It is now time for oral questions and I recognize the Leader of Her Majesty's Loyal Opposition. Thanks very much, Speaker. Speaker, my first question this morning is to the Premier. I think it's pretty positive that Ontario is finally joining the rest of the world and receiving vaccinations. That's a positive thing. But questions still remain about the, you know, the fair inoculation process, whether the inoculation process here in our province is actually going to be, you know, done fairly. And I asked the question this morning because I think there are still lots of questions that are, you know, swirling out there in Ontario about how this government intends or whether this government has a plan to actually make sure that those folks who need the vaccines the most are in fact going to get them first as opposed to folks who are going to decide to Q-jump. Mr. Prime, the Minister of Health. Thank you. Well, I thank the Leader of the Official Opposition for the question. There is a plan that has been developed that was based on the work of bioethicists. We did receive recommendations from them. The plan that has been developed is based on age and risk and making sure that our most vulnerable receive the vaccines first, which is why we have vaccinated the people who want to receive them in long-term care homes and 80% of them have also received their second vaccine. So we are well on our way to implementing our plan based on the plan that was developed with the assistance of the vaccine task force based on the work of the bioethicists who assisted us in that regard. The supplementary question. Thanks, Speaker. Back to the Premier. You know, it's really the case that the questions around people getting the vaccine who need them the first is even much more confusing because of the system that the government has put in place. It's a really confusing system. We have six regions that are going to go it alone and have their own registration. Then all of the other regions in Ontario are going to have their own registration and they're going to be a part of the provincial registration and then they're going to have hospitals registering and then they're going to have pharmacies registering. How is it that people are going to be able to understand this? Maybe folks are going to put their names on every single list, Speaker. So the question remains, how do we make sure that people who need the vaccine the most are actually going to be able to get it first when the process is such a confusing mess? Are you here? For you, Mr. Speaker, the only person that's confused is the leader of the opposition. This is the way we have to deal with it. So what I'm hearing from the leader of the opposition is maybe we shouldn't have pharmacies. We shouldn't have the family positions. We shouldn't have mass vaccination centres. No, this is all hands on deck, Mr. Speaker. And the great news is someone in Ontario will receive the one million dose today. So just to show you, everyone's pitching in and we're going to ramp that up. Along with AstraZeneca, the good news is again today at a shopper's drug mart, they're going to start pumping out the AstraZeneca and people will be getting needles in the arms. So I want to thank all the frontline folks, no matter if it's a healthcare mobile, unit's paramedics, frontline healthcare workers, mass vaccination centres, all the PHUs doing an incredible job. They're doing an incredible job. And once we get more vaccines, we're just going to ramp it up more. So thank you for the question. Final supplement. Well, in fact, Speaker, what we should have in Ontario is a plan instead of mass confusion and chaos that leaves, that likely leaves vulnerable people behind when it comes to getting the vaccinations first. And that's the concern that we have. And in fact, we're not alone in that concern, Speaker. Dr. Warner says this, if we don't, and I quote, if we don't have a structure and we don't have a framework and we don't have true criteria that can be enforced and checked, people will jump the queue and the people who really need the vaccine will be forced to wait. People who need the vaccine most in this government's chaotic plan are going to not get it. They're going to be forced to have to wait. So the question is, how will this Premier and his government make sure that people who need the vaccine the most will actually get it first? Premier, to you, Mr. Speaker, another great news. Zero mortality is a long-term care. You know, I could be quoting our doctors, too, as the leader of the opposition always quotes us, Dr. Warner. I'm sure he's a great doctor, by the way. But in saying that, Mr. Speaker, we're already rolling out the 80-pluses. And hopefully, very shortly, as we ramp this up, we're going to get through the 80-pluses. We're taking care of the most vulnerable people. And then I guess the leader of the opposition is questioning the ethics of the people of Ontario. I think that would be the worst thing in the world if a healthy young person tried to jump the queue and use the health condition for getting a vaccine. The difference between the leader of the opposition and ourselves, we actually have faith in the people of Ontario. The people of Ontario have got us through this pain loss, so we appreciate it. The next question. Once again, the leader of the opposition. Thank you, Speaker. My next question is also for the Premier. But I have to say a question. The ethics of a government that let 4,000 people die in long-term care in the first and second wave of this virus. But I do have to say, I mean, there are some positive things. There's no doubt about it. AstraZeneca's here. It's about to roll out. But the reality is everybody who needs a vaccine should be able to get it as easily as possible. And of course, as folks know, last week we talked to the government and started asking the government, rather not last week, a couple of days ago at the beginning of this week, about whether or not they're prepared to step up and support those frontline heroes those frontline workers who need to get vaccinated but can't afford to lose pay. And we asked the government to come forward and say to folks, if you need to get a vaccine, you need to have an appointment. You don't have to worry about losing a couple hours of pay. So the question is, will the government do the right thing here and make sure those frontline heroes can easily get their vaccine and protect not only themselves, but the rest of us as well. Can you hear me, Mr. Speaker? A tremendous amount. Thousands and thousands of frontline healthcare workers have already received their vaccine. We actually encourage them. My big concern is probably 40% may not get the vaccine. So we're encouraging them to come and get it done. We have sites all over the province. We'll have the mobile units going into regions. Well, the mass vaccination centers will have the family docs administering the vaccine as well and just to name a few. But talk about ethics, okay? Talk about ethics as we are working our back off. The same party, the leader of the opposition sent out a fundraising email to try to cash in on the tragedy of long-term care. Who does that? Who caches in on the tragedy of long-term care? And the same political party, the NDP, thought it would be appropriate to launch their campaign platform on the height of the second wave and using the second wave and then we're telling these long-term care to raise cash for the party. That's about as low as you can get, Mr. Speaker. The supplementary question. I think the Premier is a little confused and uncertain about the question I'm asking. I'm talking about frontline essential workers, folks that work in warehouses and in factories, folks that have been there begging groceries and working in community, folks that literally can't afford to lose pay to go and get their vaccine. This is a matter of fairness, Speaker. It's a matter of fairness to make sure that we do everything we can to help those workers to be able to get the time off that they need and not have to lose pay. So it's something that is not only about fairness, but it also makes sense. In fact, New York just passed legislation this week to give workers, all workers the time off with pay to go get their vaccine. Why is the Ford government turning their back on hardworking people, on frontline essential workers, on heroes, not only in terms of not giving them paid sick days, but not giving them the paid time off to go get their vaccines? Well, Mr. Speaker, I'll repeat what I said earlier on. Tens of thousands of frontline healthcare workers are getting their vaccinations. As a matter of fact, I talked to numerous CEOs of hospitals and people are just getting them at the hospital. They're getting vaccinated right there.  But, Mr. Speaker, there's going to be vaccination centers open up right across this province, seven days a week, in a wide range of different areas to make it very convenient for these healthcare heroes to get vaccinated and even in long-term care. I know firsthand many, many of them, probably the vast majority of the PSWs there, were in line up at the long-term care and they were getting vaccinated. I think, I truly believe, leader of the opposition, is blowing this way, way out of proportion. Matter of fact, maybe she should do a little due diligence and find out how many actually are getting it at their place. Thank you. And the final supplementary. Mr. Speaker, maybe the Premier doesn't understand what an hourly-waged worker has to go through to try to meet the bills. I mean, I think that's what's going on here. No concept. Mr. Speaker, I'm talking about essential frontline workers in all kinds of workplaces that were working while the rest of us were able to stay safe at home. These are workers in places like Scarborough, Brampton, Etobicoke, Rexdale, all around the province. These workers were working and still are working and need to be given the opportunity to take time off without losing pay to get their vaccine. It is a matter of what people deserve in terms of our thankfulness for the work they've done.  So will this Premier support this? I don't understand why he is so unwilling to support those essential frontline workers all around our province who have been there for us in every workplace. Just give them the time off with pay to get their vaccine so all of us can be safer and we can stop the spread. Premier? Thank you, Mr. Speaker. Again, rather than playing politics on the backs of our healthcare heroes, as the Leader of the Opposition did with our long-term care tragedy throughout this province, these frontline healthcare heroes at the hospitals that I've talked to and I've talked to dozens of them, more than dozens. They're getting it done at the hospitals. I've talked to long-term care. Dozens, more than dozens, are getting it done right there at the long-term care. So we encourage the hospitals to continue protecting their frontline healthcare heroes, no matter if it's a long-term care or hospitals or any other area. We're going to continue doing it. I know our frontline first responders, they're getting taken care of as well. So we're covering all the bases, but it's not about us, Mr. Speaker. It's about all the people pitching in. Every single person, no matter how small, how large it is, everyone's pitched in Ontario, and we're doing so much better than the rest of the world and the rest of North America. We're going to continue on the path of recovery. Thank you. Thank you very much. Next question. Member for Essex. Thank you very much, Speaker. My question this morning is to the Premier. There's a report that's breaking or broke, rather, this morning on the CBC that shows that the ultimate reason the Premier is paving over wetlands and pickering seems to be for a giant Amazon warehouse. The main developers, the triple group, are looking to cash in on skyrocketing property values if they get their way. And they're making sure that this Premier knows that they're real close tight buddies because they cut the party, the PC party, a check for $5,000 just a couple of weeks ago. More than a coincidence, Speaker.  Yesterday, the Premier said he wants even more ministerial zoning orders. He will not put a stop to this. Speaker, why? Is this government bending over backwards to build another warehouse on top of protected environmental wetlands? Mr. Speaker, I always stand behind the MZOs, as all these other parties, as they change the green belt 17 times the NDP and the Liberals. Guess what, Mr. Speaker? We're expanding the green belt. We will not build on the green belt. We'll make sure we protect the green belt, unlike the NDP and the Liberals did for 15 years taking care of their developer buddies. But let me tell you something, Mr. Speaker. What I'm hearing from the opposition that the 1,000 affordable homes that we gave an MZO, we shouldn't do it. The MZO we're giving and putting homes in Hamilton, the leader of the opposition, I should call the people that are going to be in those homes and say, guess what? The leader of the opposition doesn't want it. And as for the 26,000 new jobs through the MZO and thank God, Amazon's building and expanding here along with other companies throughout Ontario, what should I do when we get through the recovery? Say no, let's go through the process that will take four years and everyone's sitting in the unemployment lands. You know, unemployment line, I should say. That's what the NDP believe in. Socialism, socialism doesn't work. Freedom, democracy, entrepreneurship works. Thank you very much. Thank you. Order the supplementary question. Speaker, no one in this province should be left wondering whether projects are being sold for political donations to developers. I feel the member has crossed the line. He's imputing motive, must withdraw.  But it's pretty apparent that the Premier will move heaven and earth to get these folks what they want. This is about a company whose owners donated big political cash in order to make millions of dollars on land speculation. Why is this Premier in the middle of this pandemic so ready to do anything he can to build a warehouse for his donor buddies? Premier wants your applause. Mr. Speaker, I have to laugh when I hear him speak. I don't even know who the heck the developer is to be very frank with you. But as a matter of fact, I'm just reading off my notes, the developer, whoever this person is, actually donated to Stephen DelDuca's writing, specifically to him, and also totaling over $20,000 with the donations from the group since 2014 and then including political donations. As I'm seeing this, Mr. Speaker, I'm reading off notes. Someone could give me a ton of money to figure out who this is. I don't have a clue who this person is. But anyways, in saying that, Mr. Speaker, let's be very clear this is about creating jobs. It's not about donations. Maybe they could be bought. I can't be bought. Neither can our party. That's the Premier to the floor. The next question. Member for Perth Wellington. Thank you, Speaker. Speaker, my question is to the Minister of Municipal Affairs and Housing. Minister, I know that the opposition fails to understand why you issue minister zoning orders. These are local priority projects that municipalities identify to play a key role in the province's recovery. Projects like affordable housing and long-term care beds. Members of this House need to better understand how involved and engaged municipalities are throughout the ministerial zoning order process. Will the minister speak to the typical process working with municipalities that leads to an MZO? The Minister of Municipal Affairs and Housing. Thanks, Speaker, and I want to thank the member for Perth Wellington for highlighting this very important topic. Our government has been clear that every single minister zoning order issued on non-provincially owned land has been at the request of the local municipality full stop. Municipalities are in the driver's seat, not us. But, of course, a municipal request simply starts the process for the government. We need to do our due diligence. For example, we've been clear that we are expanding the green belt and will not develop any part of it. That's why I've rejected nine different MZO requests from municipalities that would have allowed development in the green belt. The supplementary question. Thank you, Speaker, and thank you, Minister, for that answer. I'm proud to represent made multiple requests for you to issue an MZO to allow a glass manufacturing plan. But following the concerns from residents, the company decided to suspend the proposal indefinitely. Then on Monday, the City of Stratford passed a council resolution asking for the minister to revoke the MZO. As a former municipal councillor myself, I have always encouraged local decision making. I have always respected the role of our elected municipal councils. And I know you've been clear that municipalities are in the driver's seats. Given this new request, will you revoke the MZO in Stratford? Thank you, Speaker, and again, I want to thank the member for Perth Wellington for the question. I also want to thank him for his letter that I've received. Our government has been always clear that we are committed to working with our municipal partners to advance their local priorities. Our government has been clear on that matter, and I want to reiterate that every single MZO issued on non-provincially owned lands has been at the request of the local municipality. Given that the City of Stratford no longer wishes to have the MZO in place to allow for the proposed development, I will be issuing the required 30-day public consultation notice to revoke this MZO. Thank you. Thank you. The next question member for Brampton East. Thank you, Speaker. My question is for the Premier. It has been months since Ontario has received vaccinations. Brampton is one of the worst-hit cities in this entire province by COVID-19. Yet the Premier has failed to give Bramptonians the details about when they're going to receive the life-saving COVID-19 vaccine. Frontline workers, seniors, at-risk communities don't know when or how they're going to be getting their vaccine. Now, Brampton has been a COVID-19 hotspot for months with no support from the Conservative Government. The healthcare crisis at our single underfunded and overcrowded hospital was bad before COVID-19 and it's worse now. Despite the fact that there's a light at the end of the tunnel with the COVID-19 vaccine, Bramptonians are still being left in the dark. Why does this Premier think it's okay to leave frontline workers in the dark and refuse to get Bramptonians the details that they deserve to know about the COVID-19 vaccine rollout? Premier. Through you, Mr. Speaker, I had a great conversation with the Mayor of Brampton. He was thanking us for all the things we're doing for Brampton and opening up William Osler. They're already on their way and vaccinating people 80-plus which they're doing a great job and throughout Brampton and if you look at the numbers, we're really focusing and it's been very transparent on the hotspots and Brampton was one of the hotspots so it was the Tobacco North and so was and so on so forth but we focused on Brampton and they per capita ended up with more vaccinations than a lot of regions and a lot of regions are wondering why Brampton why not me so on so forth but it's a hotspot so we focused on it so I appreciate the Mayor reaching out and having a great chat but you know something, Mr. Speaker we have some great news coming to Brampton on a couple fronts. I just can't wait till the budget rolls out and I look forward to taking over the three in the next election. Thank you, Speaker back to the Premier. The Premier loves to pretend to care about frontline workers but in cities like Brampton and others across Ontario where workers, frontline workers are risking their lives every single day going to work moving our economy they've been given no details on when they're going to receive the COVID-19 vaccine the people of Brampton and folks across Ontario they've done their part they have gone through the hardest months to stop the spread of COVID-19 and now they expect the Premier to do his job and prepare for this critical moment of the COVID-19 vaccine rollout. If this Premier actually cared about frontline workers then he would immediately provide the details for the COVID-19 vaccine rollout now. Why is the Premier keeping communities that have been the hardest hit by COVID-19 like Brampton in the dark about the COVID-19 vaccine rollout? Premier? I appreciate the question from the opposition we're rolling it out big time in Brampton and there's no secret they're getting more than anyone now the good news is the family physicians in Brampton they're going to get the AstraZeneca so we have the mobile units in there we have the mass vaccination centres we have the PHUs going full steam we have the hospitals as well pitching in and they're doing a great job in the hospitals as well so we're throwing everything in the kitchen sink in the Brampton and you're going to see the numbers start coming down the people of Brampton are incredible I lived there for five years that's where I first moved when we got married so I have a really close spot in my heart for the people of Brampton so thank you for the question the member for wealth Good morning Speaker my question is for the Premier wetlands protect people businesses infrastructure and property from flooding they clean our drinking water they keep the Great Lakes clean and wetlands do all of this for free if we don't pave over them yet the government is ripping up environmental protections to destroy the Duffins Creek wetland these extreme actions are for what Speaker an Amazon warehouse an Amazon warehouse destroying wetlands for an Amazon warehouse pulling out all the stops for an Amazon warehouse so Speaker will the Premier prioritize the people over Amazon by revoking the MZO to destroy the Duffins Creek wetland The Minister of Municipal Affairs and Housing Speaker the MZO requested by the city of Pickering supported by the region of Durham would help create over 10,000 jobs and boost the economy in that region we are as a government supporting these local municipalities the proposed change will ensure that priority projects that play a key role in the province's economic recovery located outside of the green belt do not face unnecessary barriers and delays after an MZO has been made this particular case that the member speaks about the proponent and the TRCA have entered a new agreement that will ensure the creation of ecological benefits that will meet or exceed the loss of the natural environment system this is a project that the region and the municipality have asked our government to provide and we've extended an MZO for that purpose at their request the supplementary question Speaker the city of Ajax which is directly affected by this decision has come out opposing this MZO we have the TRCA if you look at their report says they've issued a permit under duress and there's nothing that can be done to prevent or to fully prevent the damage that the government is doing with this MZO and now think about what small business owners must be thinking about you know first the government kept big box stores open and allowed them to sell essential goods why small businesses were closed now they're small business are having to compete with Amazon and the government is pulling out all the stops for an Amazon warehouse so speaker I'm asking the government will the minister will the premier put the people of Ontario first put small businesses first put the protection of our communities first by revoking the MZO that will allow the destruction of the lower Duffins Creek wetland Mr. Minister Mr. Minister first of all I'm not going to speak ill of a company that provides hundreds and thousands of jobs in the province but I am going to go back to the members question regarding this site the Ajax request happened after the city of Pickering and the region of Durham made the request to the government for the MZO I've talked about the proponent for the site in Pickering that he has an agreement with TRCA to provide the replacement of wetlands I also understand that since that time the mayor and the town of Ajax have put a request in regarding their property and understand that they were in strong opposition to the Durham live site I was sort of surprised to see it a speaker given the fact that Duffins Creek directly runs through the Annandale golf course which is the subject of this however municipalities do make these requests and today we are obviously under active consideration of any request that a municipality gives us thank you for the question the next question is for Flamborough Glanbrook and my question is to the minister of colleges and universities the parliamentary assistant to the minister represents Peterborough and that's why I'm sure he was very happy to hear that our government is investing $695,000 to increase mental health and addiction services for students attending Trent University and Fleming College this was excellent and welcome news as we know that students at colleges and universities across Ontario have had their mental health negatively impacted by the COVID-19 outbreak even though the majority of students are not on campus the government has a responsibility to make sure that our students are getting the support they need to succeed while attending college or university can the minister tell us what our government is doing to support mental health services on campuses and for students thank you very much Mr. Speaker and thank you to the member from Flamborough for that important question on mental health she's right, COVID-19 has been a very challenging time for students across the province of Ontario and that's why I was so proud to join the member for Peterborough and the minister of infrastructure for a historic announcement of over $695,000 to increase mental health services for those students attending Trent University and Fleming College Mr. Speaker, as I mentioned last week this funding will be used to enhance important mental health supports for students like increased access to mental health practitioners increased access to crisis counseling mental health planning additional FPHL counseling international counseling peer support etc this is critical supports for our students at a time when they need it most but Mr. Speaker, our commitment goes beyond our post secondary schools in Peterborough across the province we've made a historic $26,000,000 investment into mental health supports for students and I'll expand more on that in the supplementary thank you Mr. Speaker thank you Mr. Speaker and parliamentary assistant for the update we know that before the COVID-19 outbreak students on college and university campuses were increasingly facing mental health challenges according to the last national college health assessment survey of the Canadian student population in 2019 52% of students reported feeling depressed and that compares to 46% in 2016 69% experienced anxiety 12% of the students had considered suicide compared to 14% in 2016 and 2.8% of students reported having attempted suicide Speaker, those statistics are alarming and must change I hear in my constituency all the time from students and family members about the need for greater on-campus supports what is the government doing to address these concerns across Ontario's post secondary campuses and again thank you to that member for this important question as I mentioned this government's made a historic investment of over 26.25 million in mental health supports for post secondary students across the province of Ontario that's a 10 plus million dollar increase from last year at a vital time for students this investment supports a number of new and ongoing initiatives Mr. Speaker and that includes mental health grants to publicly assisted colleges, universities and institutes the good to talk mental health helpline for post secondary students new investments to support partnerships embedded in local communities to support student needs arising out of COVID-19 and a new virtual mental health app this premier recognises the challenges students are facing that's why we stood up on this historic 26.25 million dollar investment we've expanded the virtual learning strategy to support students with a 50 million dollar investment and 164 million dollar investment to expand capital supports for our colleges and universities next question for Hamilton West my question this morning is for the premier the environmental bill of rights provides Ontarians with essential protections yet this government has repeatedly and shamelessly violated this legislation in fact there's a letter from me on the minister of the environment's desk with these concerns late February big developers drop donations into PC party coffers and just days later magically this government tabled legislation and regulations to try to stop a lawsuit and pave over an environmentally sensitive wetland at Duffins Creek now there are concerns schedule 3 of bill 257 could violate the province's own environmental bill of rights especially because there was no consultation particularly with indigenous peoples why just days after taking big developer donations is the premier plowing ahead with a plan that could violate Ontario's environmental bill of rights Mr. Secretary again I want to correct the record of the member opposite every minister zoning order that our government has done on non-provincial lands has been at the request of the local council in fact the premier was absolutely correct this morning a speaker and he indicated that we did receive a request from the city of Hamilton for an affordable housing project in that community I want to thank MPP Skelly for making that announcement on my behalf again speaker the process is simple the municipality makes the request to the government and the government considers it there is no other process as the member opposite alludes to municipalities are in the driver's seat speaker mind the house that you can't correct another member's record you can correct your own supplementary question Mr. Speaker thanks for that mansplaining order order can ask the member to take your seat order can ask the member to withdraw Mr. Speaker you will know that Ontarians are outraged that the premier is pushing everyone aside and plowing ahead with this development rather than protecting the natural wetlands and now this government is prepared to rewrite laws retroactively just days after receiving developer donations Ontarians know that the environmental bill of rights enshrines their rights to comment and be notified proposals that impact the environment. Once again, it looks like this government broke our environmental laws. Will the government do the right thing and pull back from this disastrous plan? Thank you, Speaker. You know, again, our government has been crystal clear that municipalities are the ones who make the request for the MZRs. Not a proponent for a particular development, but the local municipality. As well, again, through you, Speaker, to the environment critic for the official opposition, I've denied nine requests from municipalities because the proposal included development of the green belt. And I have been on behalf of our government extremely clear that we will not accept a proposal to develop in the green belt. In fact, Speaker, we are involved. The member opposite talks about consultation. We're involved in a historic consultation on growing the green belt, which I hope based on input from Ontarians that we will have the situation where we will grow the green belt to a level that we haven't seen since it was created in 2005. So we encourage members from all sides of the House to participate in that consultation opportunity. And again, Speaker, through you, I want to thank the member for the question. The next question, the member for Glen Gary, Prescott Russell. Thank you, Mr. Speaker. Mr. Speaker, despite the claims of government members, things are not going well inside of it. Laurentian University, with its extensive French language program and designated under the French Language Service Act, is being restructured by Bay Street bankruptcy lawyers. And yes, Bay Street technocrats will determine the future of one of Northern Ontario's most important institutions. Worse yet, it is Bay Street that will decide the fate of the status of French in Northern Ontario. Laurentian University has long been designated under the Act, Mr. Speaker. Under the Act, the government has a legal obligation to provide the funds required for Laurentian to comply with the French Language Services Act. Yet, I'm told that this government is still not meeting its obligation. My question is simple. Can the government confirm today in the South that will provide Laurentian University with a funding required to comply with the French Language Services Act? Thank you. Thank you, Mr. Speaker. And I thank the member opposite for that question and for her concern. Mr. Speaker, I do find it deeply concerning that that member opposite is referring to our judicial system referencing Bay Street. We have a proud history in this province of an independent judicial system. This matter is before the courts. As I've said previously, Mr. Speaker, this government does find that the reality at Laurentian University deeply concerning. We've been working to ensure that the students have access to the supports that they need, that there will be continuity of learning, Mr. Speaker. As this matter is before the court, I will provide a little more in the supplementary, but it isn't appropriate to comment any further as this matter, as I said, is before the courts. Thank you, Mr. Speaker. Supplementary question. Thank you, Mr. Speaker. Quite frankly, that's not an acceptable answer because it's not about the matter being before the court or not. It's about the government respecting the French Language Services Act. That's separate of what's going on. Mr. Speaker, we know that the government just realized that the French Language Services Act exists, even if it's before my birth, but the government must respond to the question, frankly. Mr. Speaker, in order to comply with this act, the government must provide Laurentian University with necessary funding to offer quality French language post-secondary programs in Northern Ontario. Will the government comply with the French Language Services Act? Yes or no? Thank you, Mr. Speaker. Mr. Speaker, we will take no lessons from that member and her party after decimating the post-secondary sector, Mr. Speaker, after on the backs of students over a decade leading to some of the highest tuition costs in the country, Mr. Speaker. We put students first with a historic 10% reduction. Mr. Speaker, we've invested more into Laurentian University with stable supports of over $80 million a year. We've invested in the Northern Ontario Special Purposes Grant, $6.1 million per year. Graduate Expansion Grant, $7.9 million per year. We've stood to support Francophones across the province. In fact, it was this government that launched a university governed for and by Francophones in the province of Ontario. So we'll take no lessons from that member opposite, who's now part of the Independent Party on how to work collaboratively with partners in the post-secondary sector. We will continue to support students in this province and in... Order. The next question, the member for Perth Wellington. Thank you, Mr. Speaker. Mr. Speaker, last week members of this House debated a motion on the importance of the Line 5 Pipeline. We discussed the impact of Line 5 on our province's economic future, energy security, and its importance to many sectors, including manufacturing and agriculture. It is clear, Mr. Speaker, that Line 5 isn't just a pipeline. It's a lifeline and one that supports thousands of people who work in well-paying, high-skilled jobs that help produce products we use every day. Most importantly, it is a supply that would be very hard, if not impossible, to replace if the pipeline shudders in May. Will the minister inform this House about the government's efforts to ensure the continued safe operation of the Line 5 Pipeline? Good question. Associate Minister of Energy. Thank you very much, Mr. Speaker, and I'd like to thank the member for Perth Wellington for his question, all of his dedicated work on behalf of his constituents. Mr. Speaker, we've had two important debates over the past two weeks, and I thank colleagues on this side of the House for taking a strong stand on this important issue from day one. I'm proud that our government is fighting to ensure the continued safe and responsible operation of Line 5. We know that as many as 30,000 jobs are at stake and they're worth fighting for. I'm glad that the official opposition finally realized that it is appropriate to fight for families and jobs, and joined us in supporting our motion on Line 5 that recognized pipelines as the safest way of transporting energy resources. All of us have a role to play in advocating for these jobs to stay in interiors and recover from this pandemic. Mr. Speaker, and I can assure the member that this government and this premier will never stop fighting for those jobs. Thank you, Speaker. Member for Perth Wellington, that's your question. Thank you, Mr. Speaker, and I want to thank the minister for reiterating the importance of Line 5 to our government. I know that the minister has been a steadfast advocate since day one. Mr. Speaker, we know that the continued safe operation of Line 5 is not just important to Ontario, but to our whole country. I know that my colleagues and I have been writing to their federal counterparts to advocate on this important issue. Can the minister please tell this house what he's heard about the federal government's response to the Line 5 issue? So should Minister of Energy to reply? Thank you, Mr. Speaker. And as a member from Perth Wellington knows, our government has taken a Team Canada approach on this issue. We've been advocating nonstop for the continued safe operation of Line 5 since November. As the member said, many of us have written to our federal colleagues. In addition to the Premier's advocacy, both the Minister of Energy, Mines and Indigenous Affairs and the Minister of Labor wrote to their counterparts in Ottawa to express concerns over the impact of Line 5 on working class skilled trades jobs. And we were so relieved to hear the federal Minister of Natural Resources recently state that the Line 5 pipeline is, and I quote, a vital part of Canadian energy security and its continued operation is non-negotiable in the context of our relationship with our neighbors and friends to the south. Our government is glad to hear this news and looks forward to learning more about what the federal government has been doing on the diplomatic front to resolve this issue. And be assured, Mr. Speaker and the people of Ontario, we will continue to stand in unison and advocate with them to resolve this critical matter for the benefit of interior families. Thank you, Mr. Speaker. The next question, the member for Kiwet, now. Good morning. My question is to the Premier. Ontario plays a lot of lip service to treaties. And Kiwet, Nonga, Yamatung First Nation is part of Treaty Number 9, a treaty that Ontario signed. Ontario has a relationship with Yamatung that they like to ignore until Ontario needs an EA's approved for roads and mining. Speaker, it's humane to let people live in tents in the middle of winter anywhere. But there are multiple families living in tents in Yamatung right now today. How can Ontario say it respects Treaty Number 9 when they do nothing to help Yamatung? The Attorney General for Swans. Thank you, Mr. Speaker. And thank you for the member cross for the question. We are engaged with with our First Nations and Treaty 9 in particular on so many different files, whether it be matters of vaccines, whether it be matters of justice, whether it be matters of services across the board, Mr. Speaker. And is there more work to do? Absolutely, there's more work to do. And that's why we're engaged every single day with our with our tremendous Minister of Indigenous Affairs and our federal partners as well. So we look forward to ongoing ability to move things forward. And certainly it is something that we value and we continue to want to work with them on every solution we can possibly find. Thank you, Mr. Speaker. Supplementary question back to the premier. I'm not talking about programs and services and funding. I'm talking about treaties. This government has said that the treaty relationships are as relevant today as they were when the treaties were first signed. Speaker, Chief of Secoke Island First Nation would disagree.  Chief Alaroka stated that the local First Nations were not consulted or included in the dishes and making process. Destroying this land in the water source sends a message. And the message is there is no respect for First Nations, treaty rights in Ontario. Speaker, why does Ontario not respect treaty rights? Mr. Speaker, and again, I thank the member for his question and really his comment more than anything. The respecting treaty rights is something that the province is doing in so many fronts that we engage. In fact, we engage on issues that are outside of treaty rights. We engage on issues that affect communities across Ontario. And I'm not going to speak to any particular matter that the member is trying to advance just to say that we look forward to continued engagement. I think almost every member of our government has engaged with the First Nation on some issue of relevance. And I can tell you my department with the Indigenous Justice Division is really a shining example of the way governments can work with and inform internally in the bureaucracy as well as reaching out to the communities to make sure that their voices are heard. And we continue to look for opportunities to engage and advance the interests of First Nations through respectful dialogue at every level. Thank you, Mr. Speaker. The next question, the member for Orléans. Thank you very much, Mr. Speaker. My question is for the Premier. Mr. Speaker, Highway 413 is redundant and unnecessary. It would pave over farms, forests, wetlands and portions of the Greenbelt and cost taxpayers billions. The government knows 413 would pave over 2000 acres of class one and two farmland, some of the most productive, excuse me, in the province. They know 413 will impact the Credit River and Humber River watersheds that flow into Lake Ontario and score and are the source of drinking water for millions of residents. Order. They know that 413 will cost Ontario taxpayers $6 billion or more and only save commuters 30 seconds. We know these things, Mr. Speaker, in part because of the report commissioned by our leader and our Liberal Party, Stephen Del Duca, who led the way and shelved Highway 413. Order. And so my question to the government is, will the government do the right thing and follow Stephen Del Duca's example and cancel Highway 413? Government side, come to order. Government House Leader Derspawn. Thank you very much, Mr. Speaker. I don't even know where to begin on a question like that. First of all, let me just say this. Stephen Del Duca built an illegal pool on conservation lands. And after being a minister for so long, apparently he did not know about it. This is the same minister, Stephen Del Duca, who decided to build a GO train station where nobody wanted it, where it wasn't supposed to go against the advice of his officials. And the question is coming from a member who was in charge of a light rail system to build a light rail system that was over budget that was late and didn't work. I think the people of Ontario know they're well served by this party. Well, thank you, Mr. Speaker. My supplement is also for the Premier. The governments use the cover of the pandemic to trample local interests. They've trampled local democracy by unilaterally changing election laws. They've trampled local environmental knowledge and concerns by limiting conservation authorities. They've trampled local land use and planning policies by using ministerial zone orders to exchange wetlands for warehouses, Mr. Speaker. And more and more cities are now coming out opposing Highway 413. They know spending billions of dollars on a useless highway won't save any time, but it will take away from investments in public transit, Mr. Speaker. So my question, with a $6 billion white elephant of a highway preparing to stampede across thousands of acres of farmland, hundreds of acres of sensitive greenbelt, will the government do the right thing? Will the government listen to local leaders and stop Highway 413? Thank you very much, Mr. Speaker. I think we've already addressed on a number of occasions. We have to work, of course, closely with our partners in the area. There is an environmental assessment to do, Mr. Speaker. The leader of the Green Party actually asked about this a couple of weeks ago. And as I said then, if it makes sense, we'll do it. If it doesn't, then we won't, Mr. Speaker. But look, when it comes to protecting Class 1 farmland, this member should know that it was actually Stephen Del Ducca and his government went in office that evicted farmers from Class 1 farmland in my writing. Generational farmers who had been there for years evicted kicking and screaming from their farms so that they could build an ecological park, Mr. Speaker, on Class 1 farmland. It was that liberal government when we were trying to create the Rouge National Urban Park, the largest urban park in the country, and protect Class 1 farmland. It was Stephen Del Ducca and the liberals who refused to transfer the lands into the Rouge National Urban Park because they wanted to evict farmers and reforest the area, Mr. Speaker. Stephen Del Ducca is the worst thing for farmers. He's the worst thing for ethical government, and that's why the people who realize those things are not the time for it. Thank you. The next question, the member for Scarborough, South West. Thank you, Speaker. My question is to the Premier. Government House Leader, come to order. Constituents. Order. I apologize to the member for Scarborough, South West. I'll give you extra time. Thank you, Speaker. Constituents in my writing have been writing to my office for weeks why their parents or grandparents cannot access vaccines, asking why Scarborough is being left behind. When vaccine registrations and pre-registrations for seniors over 80 and community health workers were open across the province, in many parts of the province, in Scarborough, people were left in the dark and had no option to book for a vaccine, because the portal in our region was not open yet. People are being told, were being told that the vaccine rollout actually took place. Pharmacies are open. Racksoles open. They run out. Portals closed. And then we're hearing from word of mouth that other places like Costco hasn't opened last night. This morning they're closed just all over confusion. People are deeply frustrated by the confusing nature of this government's vaccine rollout. And frankly, Speaker, the sheer incompetence of this government. So my question is, why is the plan, what is the plan for the heart hate communities like Scarborough? And when can seniors in my writing and the rest of Scarborough, frankly, because they have four writings from the government side, can get vaccines? And why is this government turning a blind eye on my community of Scarborough Southwest and, frankly, all the writings in Scarborough, Mr. Speaker? Mr. Bell. Thank you very much, Speaker. There is one plan for the vaccination of all of the people of Ontario. It is being distributed through 34 public health units in their own way because they know the geography. They know the people that live in their writing. What happens in Toronto and the best way to do vaccinations is going to be different than in Thunder Bay or other parts of the province. However, I can advise the member, through you, Mr. Speaker, that I visited a mass vaccination site in Scarborough the other day at Centennial College. It's working very, very well. They are able to process several thousand people there. It was quite busy, but it was moving very smoothly. People there don't seem to have a problem knowing where to go. They understand it very well. The system is working the way that was intended to. Cometary question. And Mr. Speaker, I want to thank all the health care workers, all the teams that are going out and vaccinating in Centennial that the minister is talking about. And it started this week. That is the unfortunate part that it started this week. When York appeal, other regions were getting it. Scarborough did not, despite being ground zero for this province when it came to call COVID over 20 percent of all COVID-19 cases in this province are in Scarborough. And yet the amount of vaccines that Scarborough has received is nowhere near equitable amount to that state statistic. We have learned from Scarborough Health Network that they currently have 10,000 dosage of vaccines, despite having the capacity to administer 35,000 of dosage. Scarborough Health Network has one of the highest COVID inpatient numbers for every hundred COVID positive cases. Scar SHN will have five admitted to the hospital. And I'm once again asking how can this government look at the statistics, look at the reality and still continue to overlook the critical need for an equitable vaccine distribution plan. Can this government commit to an equitable vaccine rollout strategy for communities like ours? Thank you. Well, the short answer to that is yes, we do have one plan. We do have a plan that's rolling out. We are dependent on receiving vaccines from the federal government. There was a shortage of vaccines, as everyone will remember in February. However, they are starting to come into in larger quantities now. And they are being equitably distributed across the province based on population and also based on those areas that are at higher risk. There are a number of areas that are at higher risk where there are more hospitalizations, more COVID cases and unfortunately more deaths. Those areas will receive more and we anticipate that Scarborough will share in that. But there is absolutely an equitable distribution. Scarborough is receiving its fair share and we will receive more vaccine supplies coming in very shortly, which will allow us to triple or quadruple the number of vaccines that can be delivered to people every day. But we still have to wait for receipt of those vaccines through the federal government. The next question is for Ottawa. Thank you very much, Mr. Speaker. My question is for the Premier. Speaker, the Long Term Care Commission has shown on Terrians, given us a clearer picture about the decisions the government made when it came to building an iron ring around long term care homes. Testimony from Dr. Alison McGeer confirms that both the ministries of health and long term care were presented with proposals allowing hospitals to support the long term care sector by getting residents out of three and four bed ward rooms. The ministries decided not to proceed with this life saving recommendation because it was deemed to be too expensive. Commission transcripts also revealed that the minister of long term care rejected calling in the military again because it would look like a failure. So, Speaker, through you, can the Premier explain to families of residents who have lost loved ones in long term care why, if he was sparing no expense, were these proposals rejected? Mr. Long Term Care to respond. Thank you, Speaker. Those, uh, those accusations are preposterous. They are unfounded. They are, um, they are wrong. And so our government, no doubt, invested one point three eight billion dollars to shore up this sector during COVID. There is no doubt that every measure, every tool was used and that no expense was spared. Dr. McGeer herself said in testimony to the Long Term Care Commission, quote, for me, a lot of this is second hand, unquote. The suggestion that Ontario rejected proposals based on cost are completely inaccurate and misleading. And so is the call to ask the member to withdraw the member to withdraw her own parliamentary remark withdrawal. Uh, it would be helpful if the member opposite were to provide the actual proposals to which he is referring, uh, and to, uh, and for everyone to see that those were costed proposals and indicate how they, how in fact, how they were rejected. Thank you. The supplementary question. Well, perhaps in the supplementary, the minister may want to explain by her Treasury Board submissions were rejected last February. But here's the reality, Speaker. The staffing challenge grew worse after the first wave. Ontario did almost nothing to address it. You know, by comparison, Quebec went out to hire 10,000 PSWs. They only got 7,000, but they paid them to train and they deployed them in October. Would it Ontario do $14 million to train and recruit PSWs? $42 million for security guards. And then the government announced a staffing strategy last week, eight months after Quebec did essentially the same thing. So I don't know how that announcement last week addressed what happened in the second wave. Maybe the minister could explain that because it question. I don't know if they're going to do time travel, but I don't think that's going to protect or did protect families in long term care. So why were these proposals? Thank you. Thank you, Mr. Long term care. Thank you, Speaker. I like to deal with the facts and the facts are that our government through its pandemic pay was able to recruit 8,600 and additional hires to stabilize the sector. 8,600 and more. They know you're the member opposite is confused. During the pandemic pay $461 million went to create 8,636 hires for long term care. And in addition to that, we have created an across the province program for PSWs. And I will also correct the member opposite. They were not PSWs through Quebec. They were. They did not attain 10,000. They were people trained in three weeks and sent out into the field. You the member opposite needs to get his facts correct. The next question, the member for Davenport. Good morning, Mr. Speaker. This question is for the Premier Speaker. When asked on Monday about the ministry memo that was warning of looming cuts to education funding, the minister assured us that funding was up and would continue. So it came as a real shock for parents and educators in Ottawa this morning, who are waking up to news that the region's largest school board is expecting to cut at least 167 teachers this fall. Speaker, students have faced a year of turmoil and are dealing with huge challenges in learning and in their overall well-being. Now is the time for us to be putting more caring adults in our schools, not less. How can the Premier justify a return to the kind of deep cuts he was making before this pandemic began? Thank you very much, Mr. Speaker. I do know the changing position of the opposition parties. I mean, it was on February 5th where the member herself said, and I quote, the fact that they don't know where these hires occurred is deeply troubling. If they don't know where they, if they don't know, they shouldn't be in a word that I cannot say in this House, Ontarians with these numbers that they are coming up with, they're clearly not based in reality. That was February 5th and yet today the member purports that these critical investments were central to the safety of schools and with the odd not relapse. You have to choose one to the other. You actually can't have the benefit of both ways. On this side, the House, we know from day one that we hired 3400 more temporary teachers, 1400 more custodians. We know that we hired hundreds of nurses, 623 to support our schools, as well as over 400 EAs. We also know, Speaker, that before this pandemic, our premier invested more in public education, the former liberals at the peak of their spending. And we know as we look for September, we will continue to invest more than we did the year prior for areas of mental health, for learning gaps and to give young people the hope and the opportunity they deserve to reach their full potential in Ontario. Thank you very much. That concludes our question period for this morning. The Minister of Municipal Affairs and Housing has a point of order that you have. Thanks, Speaker. A point of order. I want to correct my record. In response to a question by the member for Hamilton West and Castro Dundas, I should have indicated that the government has ERO posting 019-3233 regarding the proposal she mentioned. It's posted from March 4th to April 3rd and I have a copy that I'll ask a page to send her. Thank you. Well, again, the member can correct their own record, not rebut something that was said in question period, but we have a point of order after question period. Pursuant to standing order 36a, the member for Guelph has given notice of his dissatisfaction with the answer to his question given by the Minister of Municipal Affairs and Housing concerning revoking the MZO on the Duffins Creek wetland. This matter will be debated a bit today. The Minister of Municipal Affairs and Housing has been given notice of his dissatisfaction with the answer to her question given by the Minister of Colleges and Universities concerning the French Language Services Act and Revention University. This matter will be debated today following private members public business. Pursuant to standing order 36a, the member for Glenn-Garry Prescott Russell has given notice of his dissatisfaction with the answer to her question given by the Minister of Colleges and Universities. Pursuant to standing order 35a, the member for Glenn-Garry Prescott Russell has given notice of his dissatisfaction with the answer to her question given by the Minister of Education and Research. Pursuant to standing order 40a, the member for Glenn-Garry Prescott Russell has given notice of his dissatisfaction with the answer to her question given by the Minister for Communication and Development


You know what I mean? I got my nigga Lil' Yellow from Oak Cliff here. You dig. You know what I'm saying? You dig. You used to hang with the motherfucking Get Rich click. Yeah, yeah, you did. You're crazy. Right, you know, Yellow with motherfucking Trappin' Designer. You know what I mean? That's the Yellow I know. Yeah, you dig. Used to love motherfucking Chicken from Rudy's. For sure, we still gonna eat from Rudy's. Off muscle.


Good morning and welcome to the eighth meeting of the Education, Children and Young People Committee in 2023. Our first item on our agenda today is to take evidence from the Minister for Children and Young People, Claire Hohie MSP and her officials, on the provision of early learning and childcare, specified children, Scotland amendment order 2023. I would like to welcome the minister to the committee again this morning, along with her officials, Peter Grant, head of zero to five early learning and childcare and support, and Kirsty McCarren, Solister, legal director at Scottish Government. Ms Hohie, can I invite you to speak to the draft instrument and you have up to three minutes. Thank you. Thank you very much, convener, and good morning to the committee. This amending order will increase the income thresholds from the first of April for families with the two-year-old who is eligible for funded early learning and childcare or ELC, where the parent receives a joint working tax credit and child tax credit claim or universal credit award. The relevant order currently specifies that a two-year-old is eligible for funded ELC if their parent is in receipt of child tax credit and working tax credits with an annual income that does not exceed £7,920 or their parent is in receipt of universal credit with a monthly income that does not exceed £660 per month. The amending order increases the income threshold from the first of April to £8,717 per year for households in receipt of child tax credit and working tax credits, and the universal credit income threshold will increase to £726 per month, the equivalent of £8,717 per year. We are making this change to reflect changes at a UK level. From April 2023, the UK Government will increase the national living wage from £9.50 to £10.42 per hour, meaning household income would exceed the current thresholds if they remained the same. The purpose of this order is to protect eligibility for two-year-olds who we would expect to be eligible for funded ELC as a result of their parents or carers being in receipt of those affected qualifying benefits. If we choose not to make any changes to the income thresholds, we estimate that around 1,000 eligible two-year-olds would no longer be eligible despite there being no significant difference in their household circumstances of their families. However, it is important to be clear that no two-year-old who is currently receiving funded ELC will be affected by those changes. Once a child has met the eligibility criteria, they remain eligible despite any subsequent change in circumstances. As the purpose of the amendment is to maintain eligibility, we do not anticipate a significant increase in the number of two-year-olds becoming newly eligible for the provision. We do not expect a significant impact on local authorities' ability to fund the provision within the current financial settlement. As such, there is no evidence that additional funding is required to support implementation of the amendment. The impact and uptake will, however, be closely monitored by both Scottish Government and COSLA through the appropriate mechanism, the ELC finance working group, and appropriate arrangements will be made if uptake is significantly above the level expected and local authorities' costs increase as a result. As mentioned on my previous visits to the committee to amend those thresholds, we will continue to monitor future increases to the national living wage and we will update thresholds when required in order to keep pace with those changes. Lastly, I would say that COSLA agree with this approach and that it is necessary to maintain a similar profile of eligible children. I am happy to respond to any specific questions that the committee has. Thank you, minister. I ask members to have any questions or comments on the draft instrument. Willie Rennie, first, please. Thanks very much. I have no issue with the statutory instrument, but I want to take a cheeky opportunity to ask about the uptake for two-year-olds. I know that we have made changes with the relationship with the DWP so that we can access the information. However, the gap between Scotland and England is still quite significant. It is in 2022, according to the Scottish statistics, that was 14 per cent of the total population that had access to the two-year-old provision, and in England it was 21 per cent. So, how quickly do you envisage us closing that gap? Have you seen any early evidence that we are closing the gap? The data sharing arrangements are not yet in place so we will not have seen any change in terms of the impact that those data sharing arrangements would make. We are still anticipating that that data sharing arrangement will be in place for the end of this financial year, so we are still on track for that. We have been progressing work in terms of the data sharing arrangements between DWP and HMRC and between local authorities and so on. As soon as we have all those data sharing agreements in place, the information will then be able to be shared with local authorities so that they can then access that information and write to the parents of those eligible children. Obviously, with COSLA and local authorities, we will be looking at how that uptake goes. On current figures, we anticipated that there would be something around about 25 per cent of children in Scotland that would be eligible. We have to remember that England already has those data sharing arrangements. England and Wales had those, but Scotland did not. We will be looking at that. We will be monitoring that. I am sure that the committee will be very interested in those figures and I can write to the committee to let you know when those data sharing arrangements are in place and how many families we are anticipating are eligible. We need to also remember that families have choice and not every eligible child, their parent, will decide that they want to access that uptake. Can I just take the other opportunity to ask about the provision for the deferals for four-year-olds going to primary school? We are supposed to be having from 1 August an evaluation of the pilot is due this month. Is that still the plan to have that evaluation report this month in time for August? Yes. The deferal working group, would it be possible for you to share the details of the membership of that group and how often it is made? Is that possible? I can certainly do that yet. I can write to the committee with that information if that would be helpful and then all the committee would be able to access that. I hope that I am on the right one, minister. You will keep me right. Can I ask a technical question as much as I always welcome the appearance of ministers before our committee? Is there a technical reason why we couldn't automate this process by which this automatically happens rather than having to go through this process? I think that we all agree and have always always agreed that we should engage with. School dinners are covered by this as well, right? No. No, that's the next one. I'll come back to that one then. I'll ask my question about the technical aspect. I'll pass over to Kirsty, the lawyer, who's hopefully able to answer that question. Thank you very much for your question. The order is made under the Affirmative Procedure by virtue of the 2014 act. I'll pull up the full title of that. I'll keep you right there. Under section 47 of the Children and Young People's Scotland Act 2014, the order can be made. Under section 992 of that act, this order is subject to the Affirmative Procedure. The reason why it is subject to this procedure is because there is a change in the national living wage and that is made by virtue of UK regulations. The exact amount of that is not always set out, so I think that's the reason why this is subject to the Affirmative Procedure to go ahead, so the exact amount can be taken into consideration and then the exact amount put in this order. So it isn't possible to amend that legislation so that it automatically happens? There would be a change to the legislation for that to happen. That's correct, yes. Minister, you've responded to the issues raised by the members of the committee, so thank you very much for that. We will now move on to agenda item 2. I'd like to invite the minister to move the motion in her name, S6M-07658, that the Education, Children and Young People Committee recommend that the provision of learning and childcare-specified children's Scotland amendment order 2023 draft be approved. Thank you. Does the minister have anything else that she wishes to add? Nothing more to add. Do the members have any comments? No. The question is that the motion S6M-07658, in the name of Clare Haughey, be approved. Are we all agreed? The committee must now produce its report on this draft instrument. Is the committee content to delegate the responsibility to the deputy convener and myself to agree this report on behalf of the committee? Agree. I would like to thank the minister and her officials for their participation today. We will now have a short suspension to allow for the minister and officials to leave the meeting. Our next item of business is the consideration of two pieces of subordinate legislation which are subject to the negative procedure. The first is the human trafficking and exploitation independent child trafficking guardians Scotland regulations 2023, which is SSI 2023 stroke 18. Do members have any comments on the instrument? Is the committee agreed that it does not wish to make any recommendations in relation to this instrument? Agree. Our next negative instrument is the Education Scotland Act 1980 modification regulations 2023, SSI 2023 stroke 37. Do members have any comments on this instrument? Unfortunately, the minister is not here, because it was a comment directed not at the measure itself, but in the same spirit as Willie Rennie offered his questions to the minister. My concern is that the take-up of these school meals is not what it should be, that even though the provision exists, we know that from the reports that we have that we can do better in terms of encouraging children at school to use these school meals. I wondered what the minister's thoughts were that we could do with the partners in COSLA to deal with that, but she is not here. I put it on the record that it is something that we should be concerned about. I think that there are a number of grants and provisions, including for school uniforms, that are not taken up to anything like the level that we should be in. We need to do a lot better at making people aware of what exists in terms of support for families than we currently do. I have Michael Marra first in Bob Doris. I suppose that this adjustment is about the threshold for obtaining free school meals. I wondered why we were not making a more substantial adjustment in line with inflation about the income thresholds and whether the Government had given consideration to whether that might be given the challenges that families are facing at the moment. I suppose that one thing to put that on the record is the concern about the threshold for accessibility and to say to the committee whether it might make representation or consider making representation to the Government on that basis. I think that these comments have been helpful. I think that as a committee we all are not directly related to the statutory system, of course, convener, but I think that it is helpful because we are hiding to the committee in relation to the fantastic work that has been done by the Scottish Government on free school meals and the approach to universality and the substantial increase to the school clothing that has made a real difference to constituents across the country. Massive difference, but, of course, Mr Kerr is quite right. We need to make sure that we maximise the uptake of that, so that any correspondence to Government that draws attention to the successes that those policies have been about what we can do to enhance take-up would be really, really welcome. Obviously, the way that qualification criteria that Mr Marr refers to is something that we would always welcome and kept under review, budgetary considerations to one side, of course, but we would always wish that to be under review, so I would be happy for us to write on that basis to the relevant minister, convener. Thank you, Mr Kerr. Enough of that, please. I think that in terms of the statutory instrument, I do not think that we have any comments specifically relating to that, but we do have a desire to certainly write to the relevant minister to ensure that all of these opportunities for families to support their young people through their education are maximised in terms of whether it be school meals or clothing grants. I think that we do need to find a way to cut through to make sure that everyone eligible can access that. As aware of that, are we all in agreement that we have agreed? Thank you, convener. I was just going to say that we might want to mention things like automatic enrolment. That might be helpful. We might come back in response and stuff as well, so thank you very much for those brief discussions. I apologise for cutting across, convener. I would never normally do that, but Ms Callaghan made an important point about automatic enrolment. We might want to draw to the attention of the Social Security Committee. I do not think that it is called that any more, convener, but I know that it has looked up over the years when I sat on it and chaired it at automation of benefits. Given the connection between our interests and the Social Security Committee, it might just be worth making it aware of any correspondence that we have. I apologise again, convener. Yes, your apologies are noted. Has the committee agreed that it does not wish to make any recommendations in relation to the statutory instrument? Agreed, thank you. That is the public part of today's meeting at an end, and we will now consider our final agenda item in private. Thank you and good morning.


Hi, welcome everybody to Analyzing Software Using Deep Learning. We are in summer 2020 and this is a course at University of Stuttgart. What we do in this module of the course is to look at sequence to sequence models. So this is a particular kind of neural network architecture and how to use them for analyzing software. So let me just give you a brief overview of what we want to do in this module. So as usual, there are three parts. The first one is about the architecture itself. So we will look in how sequence to sequence networks actually work and why they are useful and when they should be used. And then we'll have a look at two applications of them that use them to analyze software. The first one is about using them to find API usage sequences based on a natural language query. So basically you're asking for a particular API and how to use it by just expressing yourself in natural language. And then a model will give you an example, a code snippet that may be what you're looking for. And then in the third part, we will look at interpreting Python programs. So it's kind of a crazy idea where we are training a model to interpret a program. So to basically execute a program and tell us what results it will produce. All of this is based on the sequence to sequence networks. So we'll start by looking at what these networks are actually about. All right, so what are these sequence to sequence models? So the basic idea is that you have a sequence of items that you want to translate into another sequence of items. These items can be many different things. So you can use this overall architecture for many, many different purposes. But the basic idea is always the same, you have a sequence of something and you want to translate it into another sequence of something. So just to give you an idea of some of the applications of this kind of model, beyond what we will discuss in the rest of this module of the course. So here's a list of a few of the applications where sequence to sequence models are used for. So one, and it's maybe the most popular at all, is to translate between different natural languages. So in that case, the input sequence would be, say, a sequence of words in French and the output sequence would be a sequence of words in, say, English. Another example is to generate image captions. So in this case, the input would be some representation of an image. For example, a sequence of pixels and the output would be a caption. So a sequence of words that describes what is on the image. Yet another application is to summarize videos into texts. In this case, every item in our input sequence is a frame of the video. So basically one image that is part of this video. And then what the model does is to summarize what you see in this sequence of images into some text, which is then emitted as a sequence of words. And finally, a fourth application that sequence to sequence models are also used for is to answer natural language questions. So here the input is a sequence of words and the output is also a sequence of words that hopefully answers the question that is asked in the input sequence. So let's have a look at how this architecture, this sequence to sequence architecture typically looks like. So I'll start by giving an overview of the architecture. And then after that, we will look into some of the components of this architecture in more detail. So at a high level, this architecture consists of two sub-networks, if you want, or two neural models that are part of this overall model. So one is the encoder, which is essentially taking the input sequence and then encodes it into a vector representation. And typically, this is implemented as a recurrent neural network, as an RNN, which we have already seen in the past module of this course. And then what the encoder does, given the input sequence, is to encode it into a single vector, which is called the context vector. Let me first add the input. So the input is a sequence of some items and let's say the length of this input is m. And then what the encoder does is to summarize this input into this context vector, which may have any size. Typically, it's a relatively short vector of maybe 100 or 200 numbers. And then, given this context vector, the second main component of this sequence-to-sequence architecture is a decoder, which typically is also implemented as a recurrent neural network. And what this decoder does is to take the context vector and to emit a sequence, which is then the output sequence of this whole model. And this sequence may have length n. So what you notice here is that m and n are different letters. And the reason is that they may actually also be different length. So m does not have to be the same as n. So you can have an input length that is different from the output length. So to illustrate this, let me just give you a simple example, which is not related to software, but is related to one of the other applications of sequence-to-sequence models. And then we're translating natural language from one language into another. So let's say our input sequence is a sentence in German. And let's say it's this extremely important German sentence Staubsaugers in And let's say we want to translate this into English, then the output sequence could be something like vacuum cleaners are noisy. And what you see in this simple example is, first of all, that both the input and the output are sequences, namely sequences of words in this case. And you also see that the length of these sequences may differ, because the input has a length of three and the output has a length of four. Now, given this overall architecture, one question you might ask is how all of this is trained. So one option would be to train the encoder and train the decoder separately and then to stitch everything together. But what we do here instead is to train both networks jointly, which has the big advantage that the encoder and the decoder basically know what the other one is doing. So the encoder will encode the input sequence into a context vector that the decoder is able to understand. And to get this, the key idea here is that both networks are trained jointly. And the whole goal of this training and the reason why we have this context vector in the middle is that the context vector essentially summarizes all the input. And it does not just summarize it in some way, but it summarizes it in a way that is suitable to generate the output sequence. And that also means that, for example, some details of the input that are not needed to reduce the output may not be part of the summary because the context vector only needs to provide the information that helps the decoder produce the right output sequence. So yeah, so the summary must be suitable to generate the output sequence. All right, so this is an overview of the sequence-to-sequence architecture. And next, let's look into some more detail of how this encoder and decoder really works. So let's start with the encoder on N and how this component of the sequence-to-sequence model works. So the encoder is a recurrent neural network. So this will be a bit similar to something we have already seen in another module of this course. And similar to what I did previously, I'll now again show you the time unfolded representation of this network where we basically see the different steps that this network is taking given the different items in the input sequence. So the input is split into different items. So we have some item x at time t minus 1. And then we have another input that comes in at time t. So this is x of t. And then this goes on and on until some time point tau where t equals tau just means that this is the final time step. And when I say time, I do not really mean time as an wall clock time, but this is really about the sequence of items that we get as an input. So tau means this is the last item in the input sequence. And now with each of these time steps, we have a hidden layer inside our R and N. And the input is combined with the state of the hidden layer that we get from the previous input that we've seen. So at t minus 1, this means we are basically producing h of t minus 1 given what we get from the previous step. And this is done based on two matrices that basically control how the inputs are handled in order to get the next hidden layer. So we have this matrix w here and the matrix u here. And we'll see in a second how this really is put together. Then a time step t, the same happens basically again. We have this h of t, which now takes the h of t minus 1, combines it with w and the same happens down here with the input x, which is then combined with u. And this goes on and on and on until we reach the last time step where we have this h of tau. And the final output of this h of tau is then again multiplied with another matrix called v. And this gives us a vector called y of tau. And this is the vector that we will eventually use as the context vector of our network. So the idea is that this output vector here is the fixed size vector that represents the entire input sequence. I'll just mark this with some color because then we can use it again on the next slide where this vector will be used as the input to the decoder RNN. Now I've basically given you a nice figure to show how this RNN works. Let me also just briefly give you the equations to really see how these different values are computed. For example, we take the hidden vector h at the time step t. We take some activation function, for example, 10h, and apply this to the different inputs that are given into the step. And this is the h, so the hidden vector from t minus 1 from the previous time step multiplied with w. We also have u multiplied with our input at this time step, so x of t. And then there also is some bias added to all of this. And then eventually to get y of t, or actually it's y of tau because we do this at the very end, we take this other matrix v multiplied with h of tau, so the final hidden state plus some other bias, which is called c here. Of course this doesn't have to be 10h, so basically this function here could be any other activation function as well. So now you've seen the encoder RNN and what it produces is this little vector that I've marked with pink color, that is the context vector, which summarizes all we know about or all we need to know about the input sequence. Now the second component of our sequence-to-sequence architecture is the decoder RNN. And let's have a look at how this works. So what it gets as an input is this vector, which was previously called y tau, but here it's called x because now it's the input to this decoder model. Just to show that this is actually the same vector as what we had before, let me just mark it again here with the same color. So just going back, so this is exactly the same pink vector that we have obtained as the output of the encoder RNN, which now here serves as the input to the decoder. So what we want to eventually get as the output of the decoder is a sequence of output items that each are represented as one vector. So we will have a time step t minus 1, some vector y that is produced, same for t, so we have y of t, and then same for y of t plus 1. And actually this goes on and on and on until we are at the end of the output sequence. Now how are these outputs produced? Well, again, there's a hidden state in our recurrent neural network and for every time step, you basically have one state of this hidden vector h. So we have an h of t minus 1, and it takes our input x as one input. It takes the previous hidden state as another input and then uses this to produce the output at this time step. All of this is controlled by different weight matrices as usual. So there's a weight matrix that is multiplied with the input x. This is called r. There is a weight matrix that is multiplied with the previous hidden state. This is w prime. And a weight matrix that is then multiplied with the hidden vector at this time step in order to get the output vector of this time step. And this is called v prime. And then the same basically happens for every time step. So we also have a hidden vector time t, which takes the previous state of the hidden vector and the same input x. So this input x is basically fed into the decoder for every time step again and again and again. And this then produces our output at time t. All of this is controlled by the same matrices again. And then the same also for t plus 1. And of course also for any other time steps that follow before and afterwards. So the crucial link between the dn-coder and dd-coder is this vector down here, because this is the fixed size vector that not only summarizes the input, but it's also used to generate the entire output sequence. Let me also give you the formulas for computing the values of h and also of y at every time step. So if you want to compute the hidden state at some time step t, then we again take the hidden vector of the previous time step, multiply it with w prime. We also take our input, which is multiplied with r. And then we also have some bias here called b prime. And as usual, all of this goes through some activation function, for example 10h. And then to compute the output, we now look at the hidden state at a time step t, multiply it with this matrix v prime and also add some bias c prime. And now because what we want to predict here is an item in a sequence, we basically need to give a probability distribution over a set of possible items. So the idea is we have some output vocabulary, for example, all the words we have in the output language. And in order to predict which of these words is the next in our sequence, we need to basically give a probability to each of the possible output words. And from one of the previous modules of the course, you already know how to do this. It's by applying a softmax function here so that we basically get a probability distribution as each of these output vectors y, which will then be interpreted, for example, by taking always the output item with the highest probability. So now you've seen the architecture. Let's now have a look at how this sequence-to-sequence model is trained. So as usual for training, we need some input data and as usual we here look at supervised learning. So we basically need pairs of input and output sequences. So let's say here we have n of such pairs and each pair is called xi, yi, all i between 1 and n, where xi is the input sequence and yi is the output sequence. And in order to tell the model when these sequences are over, we need to mark the end of each of these sequences with a special symbol and we just call this special symbol EOS, which stands for end of sequence. So why do we need this EOS? The main reason is that we need the output sequence or we need to give the decoder a way to tell us when the sequence is over. So otherwise it would basically continue predicting more and more words and we wouldn't really know when to stop and by giving this special symbol for the end of the sequence we allow the decoder to basically indicate that now it's enough, I've predicted all the words that I think should be in the output sequence and now you should stop. So let me illustrate this with the example of German to English translation that we have already seen earlier. So in this case one possible input sequence to train the model would be this sentence Staubsauger sind laut where each of the words is one item in our sequence and at the end we have the special symbol for end of sequence and then the corresponding Y, so the corresponding output would be vacuum cleaners are noisy so these are the individual words in the English output sequence. And here again in order to mark the end of the sequence we have this EOS at the end. So now for the model to learn how to translate the input sequences into the corresponding output sequence we need to adapt the weights and biases in our model and we do this by optimizing a given function and this function is the following so we have a specific goal for our training where we intuitively want to minimize the mistakes done during this translation from input sequence to output sequence so we want to have a minimal number of incorrectly predicted output items in the output sequence. So what we want to do here is to minimize the following function so this function looks at the probability of predicting given a particular input sequence a particular output item and this is YIT where I means this is the ith sequence of outputs that is produced so XI and YIR are one input output pair and then YIT is the teeth item in the output sequence YI and we look at this probability or more specifically at the negative log probability for each of these so this is basically for one item in one output sequence and now what we want to do is we want to sum this negative log probability over all the items in one output sequence so T is the length of each output sequence and now we do not just want to do this for one sequence but we actually want to do this for all our input output sequences from I equals 1 to N and then average over all of those so we just divide by N and this formula basically is the objective function here because this is what we want to minimize because the lower the result of this function the better our prediction is so just to have on the slides what these different symbols mean here so T is the length of the output sequences and this probability of YIT given XI is the probability of a particular word YIT given the input sequence XI so now once we have trained this kind of model what we want to do next is to predict some output sequences for some given input sequences so essentially we want to use it for translation and in many practical applications we do not just want to have one translation let's say the most likely translation according to the model but we want to see the K most likely translations for example this could be useful in case the model is wrong sometimes because then you can look at the K most likely translations and hopefully one of them is the one that you are really interested in now how can we do this because by default what a model does is to predict one output item after another for a given input sequence so we just get one sequence and this is the most likely one but we do not have a way to get the K most likely translations the answer to this question is to use something called beam search so the basic idea is that we have like a light beam that tell us what are the most likely tokens or items in the output sequence and we do not really just focus like a laser on the one most likely token but we make the beam a little wider and look at different possible items in the output sequence so specifically for every item or word in the output sequence we consider the K most likely alternatives so let's say we are predicting the first item then we look at the K most likely items for the first one and then extend the partial sequence that we get this way in K ways at every time step and at every time step we keep only the K most likely partial sequences by basically pruning away all the other possible sequences that we have already seen so that at each time step we have K possible sequences and this means we also have K possible sequences at the very last time step which then gives us the K most likely translations so let me illustrate this idea using our running example of this translation from German to English and for the example let's assume that K is equal to 2 which means we are interested in the two most likely translations so these different possible sequences that the model is considering and that we are considering here in this beam search can be represented as a tree and we start this tree at the very beginning where we haven't predicted any output word yet but basically ask the decoder for the first time hey what is the first sequence or what is the first output item that you want to predict for the given input sequence and let's say for this example we get a couple of predictions one is that the first output should be vacuum and let's say the second most likely so the probability for this prediction of vacuum let's say it's 20% and let's say there's another prediction that says the first word should be cleaness and let's say the probability for this prediction is 18% and then of course there will be many other predictions with lower probability now because K is equal to 2 we do not really care about the others we just focus on the two top most predictions now for each of those we are asking the model hey given this first word what do you think should be the next word and let's assume that in case of vacuum as the first word we get let's say again a couple of different predictions here and again we do not care about those beyond the top two because K is equal to 2 so we only look at the most likely prediction for the second word and let's assume for the example that this happens to be cleaness predicted with a probability of 25% and let's say the second most likely second word following vacuum is again vacuum let's say with a probability of 5% now this basically looks at two possible ways to continue the sequence if it started with vacuum let's now also look at ways of continuing the sequence if the sequence started with cleaness and here we would for example see that R is the most likely second word if the sequence starts with cleaness let's assume that this is predicted with a probability of 15% and let's say the second most likely option for the second word if the sequence starts with cleaness is vacuum with a probability of 7% and now because we only care at the end about the K equals 2 most likely sequences we will now prune this search space that we are basically expanding here by multiplying the different probabilities with each other so we will take the 20% of vacuum and multiply it with the 25% of cleaness this gives us the probability of this being the right path in our beam search and we do the same for all the other paths and then what we find is that out of the four options that we have on the table right now these two are less likely than the other two so basically vacuum cleaness and cleaness R are the most likely two sequences given the tree of options that we have explored so far so what we will do now is to keep only these two and then keep further expanding them so for cleaness we will ask the model hey what could be the third word if the first two words are vacuum cleaness and then maybe it tells us R with some probability and clean with some probability and some other words with some lower probabilities and we also ask the model hey what would be the most likely third word if the sequence starts with cleaness R and maybe here it says noisy would be the most likely to finish this sequence clean would be the second most likely and then there are other options as well and then again we do this pruning that we have just seen so we would basically compute the different probabilities which I have not given now for the third step but I guess you get the idea now and let's say this would remove these second options in each case which basically leaves us with vacuum cleaness R as one of the two most likely ways to predict the output sequence and cleaners are noisy as the second most likely and then this of course goes on and on and on until at some point so for each of the remaining options we always look at the two most likely ways to continue this sequence and this goes on and on and on until eventually we are reaching the end of sequence symbol which tells us that now the model thinks we are done so what this basically gives us is a way to get the K most likely output sequences without really querying the model for all possible output sequences and computing the probability for each of them because this will not really scale but instead we are pruning the search at each time step in order to just focus on the K most likely sequences at a given point alright so this brings us almost to the end of this first part in this module on sequence to sequence architectures just to make sure that everybody understood something I have a little quiz which basically gives you four sentences some of which are correct and some of which are wrong and the task for you is to now stop the video for a moment carefully read these sentences and think about which of them are actually correct and which of them are wrong alright so let me show you the solution so the first sentence is correct so this context vector can indeed be a potential bottleneck that may prevent a network from effective learning so as an extreme case suppose we just make this context vector of size one which basically means there is one real valued number that needs to summarize the entire input sequence and this is unlikely to work for any complex translation task the second sequence the second sentence the length of the input sequence must be the same across all instances of the training set this is wrong so because the encoder is a recurrent neural network and because recurrent neural networks can handle differently sized input sequences the input sequences may have different sizes and we use this end-of-sequence token to tell the model when the end-of-the-sequence is reached the same is true for the output sequence so also here the sequence length may vary across the different data points that we see because we have this end-of-sequence symbol to allow the model to tell us when we have reached the end-of-the-sequence and then finally the last sentence is true again so each instance in the training set must indeed contain two sequences namely the input and the output and the reason simply is that we here do supervised learning so we need to have examples of inputs and outputs that come in pairs so that we can train our model cool so this is the end of the first part of this module I hope you now know sequence to sequence models are and what we'll do in the remaining two parts is to look at their applications for analyzing software so thank you very much for listening and see you in the next part