It is now time for a question period. The leader of Her Majesty's Loyal Opposition. My question is to the Premier. Premier, in light of the gas plant scandal and the billion-won waste to save liberal seats to cancel the awful gas plant, we asked the House to sit longer to debate that. You refuse to do so. And I'm also worried that you're reneging on our deal. A month or so ago, you and I sat down in your office. We agreed to clear the decks on legislation that was not really focused on jobs and the economy in large part. So that would pave the way for you to put forward your jobs plan. You have to see that plan. You've moved from tending-bed legislation now to restaurant menus. But I've not seen anything when it comes to jobs or balancing the books and the province. I wrote you a follow-up letter and asking if we could sit down so I could see your plan. So let me ask you, Premier. Bottom line. My question? Why are you reneging on our deal? Premier? Well, Mr. Speaker, we did have that conversation. And the conversation went like this. I suggested that there were some pieces of legislation that we could move ahead with that we could find agreement on, Mr. Speaker, so that we could continue to have debates about some other things that maybe we didn't agree on, Mr. Speaker. And one of the things that we don't agree on is the path forward. Because I think what the leader of the opposition is suggesting, Mr. Speaker, is that we would adopt his plan to slash and cut public services in this province, Mr. Speaker. And that's not what we're going to do. So instead, what we're going to do is we're going to invest in people. We're going to invest in infrastructure. And we're going to invest in a business climate that is going to create jobs, Mr. Speaker. And, for example, we've committed $17.6 million to support regions and businesses in this province, Mr. Speaker. That's leveraged over $133.1 million in investments. And it's created or retained nearly 2,800 jobs, Mr. Speaker. So that's just one piece of the work that we are doing. And in fact, the leader of the opposition didn't support that strategy for regional encouragement of jobs, Mr. Speaker. And that is confusing at best. Thank you. Before we move on, just as a comment, I will not allow shouting people down anymore. Supplementary. You know, the Premier, maybe there's some confusion. I thought we had agreed we'd clear the deck so you could bring forward your job's plan. It seems like you wanted to clear the deck so you could bring forward legislation around restaurant menus as opposed to our vision, which is paving the way for more jobs and more opportunity for Ontarians. Premier, a million people began this week with no job to go to. They're losing hope in this great province. And I worry that your ideology blinds you to the challenges we face or what's necessary to turn our economy around. You know that if interest rates go up, that that will put another $500 million of debt interest, taking away our ability to hire more nurses or do more MRIs. So, Premier, clearly you ran to be Premier for some reason other than to have that office. It has been nine months of endless study, conversations and consultations. Where is the big plan? Where are the ideas? Where is the hope and opportunity? Premier, so on top of the regional development strategy which has created or has helped 2,800 jobs, I would suggest that the Leader of the Opposition talk to some of the folks who work in the Ford plant, because that's $70.9 million investment in the Ford plant that will protect more than 2,800 jobs and allow Ford to take part in global trade. I think he would want to support that. He also might want to talk to people in small businesses who understand that the Supporting Small Business Act is going to help them with their payroll, Mr. Speaker. It's going to allow them to hire more people. Those are actions that we're taking along with the local food act that will encourage and support more jobs in the agriculture sector, Mr. Speaker. The Waste Reduction Act, which will create jobs. So all of those are part of our strategy to make investments in people and in infrastructure and in a business climate that will allow the private sector to create jobs. That is happening, Mr. Speaker. Thank you. Mr. Speaker, we put a plan on the table to create over 300,000 jobs, good jobs and manufacturing to get energy prices under control, to lower taxes, to change the attitude of government, to get out of the way of business, to stop always standing the way of job creation and get behinds, to invest and create jobs again. And all I hear from you is more warmed over old NDP ideas that quite frankly got us into a deep ditch back in the 1990s. Let me ask you this at least. It's been a month since we agreed to clear the dachshund brought forward no plan. I wrote to you almost three weeks ago. You've not responded to my letter to meet to discuss your plan as of yet. I'm worried that you have no plan. Order. So what you said to the House today, I know the economic statement is coming shortly. Will that be a game changer for that province? Will that be a moment of truth? Will it actually, will we finally see the Kathleen vision, Kathleen Wind vision? That was a tough one. Let me rehearse that one more often. Let it try that one more often. But we actually see what your plan is because you only have two moments of budget and the economic statement every year. You waste the budget. So please, let's go to the economic statement. Thank you. Mr. President, please. Mr. President, please. I suspect that there was a reason why you fumbled over because he knows that we're not supposed to use proper names in here. And I think that's what was the problem. You stumbled over it. In my mind, all members, please, use either title or writing. Thank you when referring in the House, the Premier. Mr. Speaker, but I am not offended by the leader of the opposition calling me by my first name. Mr. Speaker, what our fall economic statement will not do is it will not adopt the Conservatives' agenda, which will fire 10,000 education workers, Mr. Speaker, fire 2,000 healthcare workers, Mr. Speaker, drive wages down with harmful rights to work legislation. The member from Chatham, Kansas, has come to order. The member from Northumberland... No, I was thinking of whether I should or shouldn't, but I will. Northumberland, 20 West. Premier. So, Mr. Speaker, we will not adopt that plan that we believe would undermine the progress of the province. Mr. Speaker would not provide for a future of well-educated workers, Mr. Speaker, would not create an environment where investment wants to come to this problem. That is what is happening now, Mr. Speaker. Jobs are being created. We're investing in a business climate that's innovative and dynamic, Mr. Speaker. Thank you. New question? The member from Nipissing. Speaker, my question this morning is for the Finance Minister. Minister, our party has cleared the decks so you can present your jobs plan to the legislature. Minister, we're still waiting to see it. You've been in office for nine months, held 100 conversations, created 32 panels, and yet there's still no plan to create jobs and kickstart our economy. But your jobs plan isn't the only thing that's AWOL, Minister. The Fiscal Transparency and Accountability Act, which your government passed, states, quote, within two years after each provincial election, the minister shall release a long-range assessment of Ontario's fiscal environment. Minister, you're two weeks late. When will you be releasing this assessment that you were legally required to release two weeks ago? Well, Mr. Speaker, I appreciate the question. I appreciate the fact that the member opposite is actually interested in knowing how to increase and promote economic growth in our great province. He recognizes that we have achieved results. He knows fully well that we've had a plan that's working, Mr. Speaker. We have 180% return of those jobs that were suffered during the recession. We are the top jurisdiction around the world exceeding our targets. We are the lowest-cost government in all of Canada and all orders of government. We have the most competitive tax regime to stimulate investment, and it is working. We have a full economic statement that's coming out shortly. We've produced first-quarter results that achieves our opportunities, and it shows the success that we had to date. And public accounts, audited public accounts show that we exceed our targets. We are coming forward with a long-term plan beyond election psychopolitics that the opposition wants to play. We're not going to, Mr. Speaker. Minister, that assessment isn't optional. You're legislated to do this, and the Act spells out the specific areas the assessment is to report on. Your predecessors actually did meet this requirement, but apparently you can't. You're running a fowl of your own government's law, but then again, we've seen the deleted gas plant's emails that breaking the law seems to be nothing new over on this side. Maybe you're working hard behind the scenes to get creative with the numbers, like you did on the gas plant, to hide your failed wage freeze, which we exposed last week. Minister, in nine months, you've put forward no plan to create jobs, no plan to stimulate the economy, and no plan to balance the budget. Do you have any plan at all to present your long-term fiscal assessment? Minister? Mr. Speaker, not only do we have a plan, we have results that are working... Minister? And the plan has been outlined a number of times which the opposition choose not to read. What we will say, and in the upcoming fall, Economic Statement will highlight some of those issues, but what the opposition must recognize is that what they talk about is actually a destructive plan. And we will not take extreme views of across-the-board cuts that will harm the sensitive recovery of our province. We have taken measures of austerity to a point that's necessary, but now we must stimulate economic growth. We will continue to invest in people. We're going to continue to invest in infrastructure and we're going to continue, Mr. Speaker, to ensure economy grows by taking up... ...the final supplementary. Let's recap the last nine months. There's no jobs planned, no plan to stimulate the economic growth, no plan to balance the budget, and no long-term assessment. It's clear that you're not up to the job on this file, Minister. It only stands to reason that Ontario's can expect another whole lot of nothing when you present your fall Economic Statement. You've shown through the gas plan scandal that your government has a lot of trouble with numbers. The least you can do is use this opportunity to finally lay out a plan to get more than 500,000 men and women who woke up this morning without a job back to work. Minister, it's obvious your fall Economic Statement won't have a real jobs plan. Will you take our plan, our 14 white papers, and use our ideas to put Ontario back to work? So, Mr. Speaker, if we recall their plan, their plan was to hide a huge deficit. Their plan was to sell assets at fire sale. Their plan was to give it away, Mr. Speaker. Their plan left a legacy of an energy problem that we're still paying for today. We have taken control, we have invested in our province, we're investing in our people, we're investing in infrastructure, and we're creating a climate of economic growth and business development with innovation. We're going to continue on that positive plan, Mr. Speaker. We are not going to fall prey to what they're proposing. Question leader of the third party. Thank you very much, Speaker. My question is for the Premier. News reports indicate that the Premier is creating yet another panel. This time the conversation will focus on so-called open government. If the Premier is interested in openness, Speaker, will she commit today to returning to the Justice Committee to explain her role in the decision that handed over a billion dollars to a private power company? Much, Mr. Speaker. I have a question from the committee. If the member has a question, I'd be happy to answer that question, but I just want to say, Mr. Speaker, that I need to know what the new information is that the member is seeking because I've accepted responsibility as a member of the cabinet that made the decision, Mr. Speaker. I've apologized a number of times. I've explained my role at every step of the process. I've explained every interaction that I've had, Mr. Speaker. I've explained my understanding of my officials. I appeared at the committee on April 30th. I've answered 207 questions in the House, Mr. Speaker. I've responded to the AG report. I've responded the day that it was tabled. So I've done all of that, Mr. Speaker. I haven't received an invitation, as I say. I'd be happy to answer a question if the member has a specific question. Mr. Speaker, people learned that liberal waste is costing them $1.1 billion. And the auditor tied that cost to decisions signed off by this Premier. The Premier wants to have a conversation about open government, but people want some answers about the sky-high price of electricity that they're paying in this province. Will the Premier come to the Justice Committee and explain why she was signing a document that was helping private power companies guarantee their profits and putting families and businesses on the hook? So I have explained my role in that process, Mr. Speaker. I have explained it in this House and I have explained it at committee. And as I say, I have a number of times explained my whole interaction and my whole role in the process, Mr. Speaker. And the reality is that when I came into this office, I said that we were going to open up the process and that is exactly what we did, Mr. Speaker. So in fact, my commitment to open government is an expression of belief that I have always held and that has been manifested by the fact that I have attended the committee that I have opened up the process. We broaden the scope of the committee and we've provided thousands of documents, Mr. Speaker, in answering the questions that have been asked by committee. So the questions that the leader of the third party are asking are questions that have been asked over and over and over again, Mr. Speaker. And they have been answered over and over and over again. If there is a new question, if there is new information that's being sought, I would like to hear that, Mr. Speaker. You know, Mr. Speaker, the Premier has claimed that she doesn't want to have this kind of thing happen again in Ontario and I can tell her neither do Ontarians, Speaker. They're tired of watching their bills go up and up and up and they want to know why, Speaker. People want to understand. They want to understand why the Premier was signing off on decisions that the auditor said that she favored private power companies. Will the Premier be coming to the committee to explain why she did it? Mr. Speaker, I have answered that question. I've talked about my role in the cabinet walk around that happened, Mr. Speaker, and I have taken responsibility for being part of a government that was in a process and was trying to avoid litigation, Mr. Speaker. We've talked. I'm probably going to ask the member from Hamilton, East Stony Creek the same question I would ask him if he was in his seat and that is to come to order, please. Thank you. And Mr. Speaker, I spoke week before last about the advice that we were given that officials advised us that waiting to relocate the plant could have been more expensive and that renegotiating was more prudent than ripping up the agreement, Mr. Speaker. And so we were engaged in that process. But the point is I have taken the member of cabinet for that decision, Mr. Speaker. I have articulated my role and that will get you thrown out. If you want to start doing that, I'll start throwing. Finish, please. 10 seconds. Mr. Speaker, and just to say that we have provided 175,000 pages of documents and answers to all of the questions that have been asked. Thank you. New question later in the third party. Well, thank you, Speaker. My next question is for the Premier. The Premier loves conversation and she has the tools to prove it, Speaker. Now there are 30 groups looking at everything from new tools and taxes to undoing the damage to the rural racing industry. Now the Premier is saying she wants a panel on openness. Will she show commitment to openness, Speaker, by coming to the Justice Committee and explaining why she signed off on this decision that clearly favored a private power company? Thank you very much, Mr. Speaker. And I, apart from the question, I just want to say, Mr. Speaker, that I think it's very, very important that government pay attention to people's opinions, that we engage with people, Mr. Speaker, that we get feedback from people outside of government. And so that is how I have operated as a politician. That is how I will have people with expertise give us advice. We do believe it's important, Mr. Speaker. We think that it's a very good thing to have people who understand a particular sector or a particular issue. As for an example, the government process, I think it's a good thing for them to give us advice on engagement with the public. And I look forward to that process, Mr. Speaker. Thank you. Well, G. Speaker, maybe the Premier and the Liberals should have been listening to the Council in Oakville back in March of 2009 when they passed a resolution for trying to be looking for some real answers about their sky-high hydro bills, not conversation after conversation after conversation. Ontario's premier was part of in her report on the Oakville gas plant. This government has created such a massive energy planning that the premier was signing documents that gave private power companies huge advantages instead of protecting families who pay the bills. Will the premier be returning to the Justice Committee to explain why she was a part of a decision? They gave private power companies the upper hand, or is her new openness panel just another question. Thank you very much, Mr. Speaker. I just want to say to the leader of the third party that, you know, I agree with her, and I have said many, many times that had we paid better attention, had we had a better upfront process in the location of those gas plants, Mr. Speaker, then we would not have made the mistakes that were made. And I've said that quite openly that having a better community process is part of what needed to happen in the future, Mr. Speaker. As for the Justice Committee, I haven't received an invitation, Mr. Speaker, but I have been to the Justice Committee, I have answered many, many questions in the house and at committee I have explained my role, Mr. Speaker, and if there is new information that's sought, I would be happy to answer that question, Mr. Speaker, but I have been there and I have not yet received another invitation. Thank you. Final supplementary. I would like to thank the President for their own self interest ahead of the interests of Ontarians. That's what Liberals do all the time. Last week, Ontarians found out that they had seen their electricity bills, going to see their electricity bills rather keep growing faster than the rate of inflation in this province. It's getting harder for them to pay the bills already, and they deserve the answer, Speaker. They deserve to know why the House of Representatives and will the Premier come to the gas plants committee and explain her decision to protect the interests of private power companies instead of the interests of people and businesses who are stuck paying the highest hydro bills in this country. I have been to the committee and I have answered many, many questions and I have not received an invitation from the committee at this point, but it has been left in disarray. There were huge investments needed in distribution, Mr. Speaker. The capacity and the generation capacity was not what it needed to be, Mr. Speaker. We have made huge improvements, Mr. Speaker. The member from Glengary, Prescott Russell will receive the same advice or the question that I asked the member from Hamilton East Stony Creek. If you were in your seat, I would tell Mr. Speaker. So Mr. Speaker, the investments that we have made in the energy system have made it more stable, Mr. Speaker, and it's work that absolutely had to be done. As far as our commitment to green energy, Mr. Speaker, that we are leaders in terms of the North American continent and making sure that we have clean renewable energy going forward, Mr. Speaker. So I'm proud of our record. I have said clearly that there were mistakes that were made and contrary to what we have done, Mr. Speaker. And that actually produces a better outcome, Mr. Speaker. That's why we're putting one in. Thank you very much. You sat at the cabinet table and signed the document which authorized your Liberal government to waste over $1 billion of taxpayer money to cancel two power plants. Over the past eight months, you have stated that your government reacted out of respect for the local community's opposition to the North American continent. 73 municipalities in Ontario have declared themselves unwilling hosts. Projects continue to be approved for communities who do not want them. Since when did a person's postal code determine whether they receive respect or contempt from your government? Tractors, excuse me. I was out in the rain with these folks on the weekend. About 200 trucks and trucks and 1 km stretch of Highway 402 to get your attention. Premier, will you recognize that awesome? Thank you. Well, I think the member opposite absolutely makes the point that I was making in response to the leader of the third party, which is that it is very important to have a good community process. And the process that the minister of energy is putting in place which identifies willing hosts and gives communities more input into the process up front, Mr. Speaker. That is exactly what needs to happen. And I would suggest, Mr. Speaker, that the work that we did on green energy has been very, very positive and take communities. If it's a test, I'll pass it. Supplementary. Thank you, Mr. Speaker. Back to the Premier.  Enough intellectual jobs because of your botched green energy policies. The audacity to announce first, last Friday, I have to tell you, Premier, my constituency assistant helped a family of seven. Their electricity had been cut off because they could not afford to pay their hydro bill. The mother called my office frantic because she had five small children and we had the threat of snow this past weekend in my riding. Thankfully, on a Friday afternoon, we were able to arrange to get the hydro back on. But for how long? Premier, where are you taking this province? Truthfully, I am dreading this winter in fear of all the people who cannot afford their hydro bills. Premier, is this what you envisioned for Ontario when you took over this role and are we to expect families not to receive the basic... Thank you. Let's not get wound up before I even get a chance to have her stand. Premier? Thank you very much, Mr. Speaker. Well, Mr. Speaker, let me just say that we have rebuilt over 80% of our electricity system because... Remember from Noura Fumblin, Quinty West is worn. Carry on. Not rebuild of 80% of the electricity system had to happen, Mr. Speaker, because when we came into office, it was not reliable. It had been neglected and that work needed to be done. On top of that, Mr. Speaker, our plan for green energy has eliminated dirty coal, Mr. Speaker. It's created more than 34,000, 31,000 jobs. Remember from Sonia Lantan is worn. Carry on. And it's generated $24 billion in investments, Mr. Speaker. So I absolutely take to heart and I'm glad that the member opposite was able to work with her constituent to make sure that her constituent had power. But that power is available, Mr. Speaker. We've reworked the energy system and we have... Thank you very much, Mr. Speaker. My question is for the Premier. Mr. Speaker, this government dealt a death blow to the horse racing industry under the pretext of OLG modernization. OLG modernization is simply a liberal code for more casinos. But Ontarians have been very clear that they don't want casinos in their communities. Last week, the City of Vaughan voted to reject being a host site for a casino and now the doors are quickly shutting to the possibility of a casino anywhere in the GTA.  Thank you, Mr. Speaker. And I appreciate the question and I appreciate the premise of the question recognizing some of the concerns that exist going forward with regards to the transformation of the OLG in our gaming. We recognize how important to be supposedly responsible. We recognize also the great degree of dividend and support that the OLG provides for schools and hospitals and investments in our communities. We also appreciate and respect municipal decisions and that's what we've done all along. Thank you, Mr. Speaker. Thank you. Back to the Premier. The slots and racetrack program brought in $1.1 billion a year in government revenue by cancelling the SARP this government has destroyed an entire industry in southern and rural Ontario for the profit of big casino conglomerates but Ontarians don't want casinos in their communities. They want racetracks. Time to admit you made a mistake reinstate the slots at racetrack program until you figure out a fair and transparent plan for horse racing and casinos in Ontario. Mr. Speaker, Mr. Вагракulture Thank you very much Mr Speaker. In fact, the plan that we have put in place is an accountable and transparent plan to the former members John Swinoblin and Elmore Liu Cannon and John Wilkinson they have worked with the industry to put in place a plan that will allow for a sustainable industry. The SARP program was neither transparent nor was it accountable so it would be for us to move back there. But, Mr. Speaker, what we want is a sustainable industry across the province and all of the tracks in the province, whether they're part of the core or whether they're part of the grassroots, we'll have an opportunity to present a business plan, work with OLG and have a sustainable future. That was our goal, Mr. Speaker, and that's what we've put in place. Mr. Speaker, my question is for the Mr. Transportation and Infrastructure. The Friday before Thanksgiving, I had the opportunity to join Mayor Watson, Members of Council and a number of colleagues from Queens Park at an event to mark the start of Boring the Tunnel for Ottawa's Late Rail project. It was truly an exciting day for Ottawa. Mr. Speaker, even with this exciting news in Ottawa, there's a lot of interest in the transit debate that's happening here in Toronto. In fact, many Ontarians want to know how the government is helping to build the future of transportation infrastructure in the province's largest city. Having said that, Mr. Speaker, residents of Ottawa South want to know how this government is going to help Ottawa move forward. Recently, Mayor Watson called for a massive transit plan to get cars off the street and citizens to the places they need to be in an efficient manner. Question, Mr. Speaker. To the Minister, what have we done to get Ottawa moving? Thank you. Mr. Transportation and Infrastructure. Thank you, Mr. Speaker. We are investing and have invested since we've come to government $1.8 billion in the city of Ottawa. I believe that is an unprecedented investment in that community, Mr. Speaker, and I think that's due to the very hard work of a number of liberal MPPs from that constituency, Mr. Speaker, who are delivering for the community. The confederation line, which the member from Ottawa South has been a big champion of, Mr. Speaker, is moving forward. It's a very significant contribution, Mr. Speaker. It is part of over a billion dollars of investment in rapid transit alone, Mr. Speaker, and $600 million just to the bus rapid transit system. Mr. Speaker, we often get asked what the jobs policy is. There's investment, Mr. Speaker, creating 20,000 person years of work in Ottawa and creating the foundation for major private sector job creation, Mr. Speaker. Thank you. Thank you. Supplementary. Thank you, Mr. Speaker. It's very good news to hear that transportation funding is a priority and that projects are underway in Ottawa. Residents of Ottawa South will be glad to know that this government is helping municipalities like Ottawa to build the transit we need. There are many small to mid-sized cities that need a steady flow of funding to finance transit infrastructure. I know that we are committed to assisting all regions and all cities to get every single Ontarian to work and home as fast as possible. Mr. Speaker, it is important to my constituents and to all Ontarians and small to mid-sized cities to know that they can count on funding to support their demands for their public transportation system. Can the minister tell us what we're going to do to the government to ensure there is steady funding to help municipalities outside the DTHA? Thank you, minister. Thank you, Mr. Speaker. If you understand the importance of infrastructure, you just have to look out the windows of the legislature. The biggest commercial boom in construction is going on in the history of the city. It is estimated, Mr. Speaker, that half of all the construction cranes in North America are at work right now in the DTHA alone. That is a remarkable record, Mr. Speaker. But it extends beyond Toronto and I mentioned the huge investments in Ottawa. Mr. Speaker, a small community like Ignace in Northwestern Ontario has clean water because of this government rebuilt its water treatment plant, Mr. Speaker. In communities as small as Burpee and Mills Township, Mr. Speaker, there is $178,000 going to build a critical road in that community that will help revitalize that community, Mr. Speaker. Answer. In Colbalt, almost $2 million is being invested right now in basic road infrastructure, Mr. Speaker. We are building jobs and opportunities across the Ontario, Mr. Speaker. Thank you. No questions from the members of my team. Thank you very much, Mr. Speaker. My question this morning is for the Premier. As you know, Premier, my Bill 74 takes a firm stand in support of Ontario workers and in support of an Ontario company. Premier, on September the 9th, you spoke in support saying, and I quote, it's about a level playing field and it's a very good example of the kind of thing where we can find agreement and we should be able to move forward, unquote. Premier, you are all in. But on October the 2nd, you stated, and I quote, I will not be supporting it, assuming that the decision is not appealed, so that's the decision, unquote. Well, Premier, you have both flipped and flopped. But the time for clarity is now and thousands of workers at Elaston are eager for your word. With the decision being officially appealed, Premier, will you assume your support of my important bill or will you resign on your word in favour of foreign corporations over Ontario workers? Thank you, guys. The divisional court has made a ruling that quashed the decision of the LRB, Mr. Speaker, so the company can continue to operate as it did prior to the LRB case, Mr. Speaker. So from my perspective, and I have said this because circumstances have changed, the urgency that was created by that Labor Board decision, Mr. Speaker, have been removed by the divisional court decision, Mr. Speaker. Thank you, supplementary. Well, Premier, just to reiterate your quote, you said it will not be supporting it, assuming that the decision is not appealed. That was your word, Premier. Your lack of leadership and lack of decisiveness has risked an Ontario success story and thousands of Ontario construction jobs. My bill 74 will maintain the status quo for Elaston and will settle this issue once and for all. Premier, you stated that you would not be supporting my bill. Assume... Attorney General will come to order. Second time. Premier, again you stated that you would not be supporting my bill, assuming it was not appealed. However, despite the appeal, you have chosen to stand with foreign construction companies instead of Ontario workers. Based on your past statements, it is obvious that your government expects the divisional court ruling to hold. Premier, when did you tell the sheet metal workers and the election workers that you expect their appeal to fail, and why do you refuse to stand up for Elaston and their thousands of employees all across Ontario? Thank you very much, Mr. Speaker. And I think the member opposite knows full well that there has been no appeal granted at this point. There's a leave to appeal before the court. I believe that the circumstances have changed. The divisional court has quashed the ruling by the OLRB, Mr. Speaker. And because of that, I believe that the urgency that was in place because of that OLRB decision is no longer in place, Mr. Speaker. Thank you. Good question. Member from Essex. Thank you, Mr. Speaker. My question is to the Premier. Speaker, last spring, well-connected insiders hired by Elaston had legislation crafted so they could escape a contract they had with their employees. The Conservatives proposed it, but the Liberals enthusiastically supported it. And the Premier agreed to speed it through this very house. Now she's scrambling to distance herself from the varied bill that she championed. Can the Premier tell us what today's position is on the Elaston bill? I think I just answered this question, Mr. Speaker, but I'm happy to answer it again. As the member opposite knows, the divisional court quashed the ruling of the Labor Relations Board, Mr. Speaker. The fact that the company can now continue to operate as it did before the OLRB ruling, Mr. Speaker. I believe changed the circumstances and we believe that the bill is no longer needed and that the urgency that was in place because of the OLRB decision is no longer there. Thank you, Speaker. The Premier's position on this has more loops and turns than a roller coaster. What's more and more clear is that the Premier will say and do anything to help the Liberal Party. First, she championed the bill, passed it unanimously and put it on the fast track. Then she tried to convince the unions to abandon their right to appeal. Then when they called her bluff, she zigzagged again and now she claims she's going to oppose it. What assurances do people have that the Premier won't flip flop yet again when the lobbyist from Alice Donne come knocking? Well, Mr. Speaker, I have always believed that if one takes a position under a certain set of circumstances and then those circumstances changed, then the intelligent response to the position. The circumstances changed. The urgency that was in place is no longer in place and so, Mr. Speaker, I believe that the piece of legislation is no longer required. Thank you very much, Mr. Speaker. My question is for the Minister of Citizenship and Immigration. The Ontario Provincial Nominee Program known as the PNP is a valuable immigrant selection program that allows Ontario to nominate economic immigrants. Member from Renfrew, that'll do. Newcomers are nominated. Oh, really? That'll do. If I have to get louder just because the member refuses to hear what I'm asking, then I will get specific. I've asked them to refrain. The member from Renfrew choosing to ignore me? Good. Please finish. Very much, Mr. Speaker. I just recently learned that the federal government has capped Ontario's yearly nomination at only 1,300 nominees. I was also surprised to learn that no new PNP applications have been accepted since August. Mr. Speaker, through you to the Minister, how is our government ensuring that we select the best and brightest economic immigrants to fill the skilled labor gaps that exist in Ontario? Good question. Minister of Citizenship and Immigration. Mr. Speaker, the member is correct. The federal government has capped our provincial nominee program here in our province in 1,300. The federal government could do better. Ontario deserves more. Ontario has little say from the federal government on economic immigrants who are selected to enter our province. Of the 99,000 people who were immigrated to Ontario in 2012, we had a selection of less than 1.5%. And that's not great because if you consider what's happening in Alberta, Manitoba and Saskatchewan last year, the Alberta government had 11% selection. Immigrant selection in Manitoba was 28% and Saskatchewan was 34%. The Ontario immigration strategy spells out the need for Ontario to have greater say in selecting skilled immigrants here in our province. By selecting highly skilled immigrants to fill positions in our labor force, Ontario will be able to grow its workforce to create more jobs in Ontario. Thank you very much, Mr. Speaker. Many Ontarians do not know that our province is not being given its fair share of PNP spaces. I understand the minister has written to his federal counterpart to request additional PNP spots. Many employers and investors are looking to come to Ontario and will be glad that our government is advocating for more selection through the PNP program. Mr. Speaker, through you to the minister, could you please address the misconception that our government is committed to Ontario negatively contributes to our economy and to more unemployed Ontarians. Thank you, Mr. Speaker. I would like to thank the member from Grampton Lester for his great question. Our government is committed to the economic growth and believes that an educated, skilled and diverse workforce in Ontario is one of our greatest strengths. A diverse economy in our province . Since 2010, Ontario has nominated more than 2,000 international PhD and master students for permanent residency through our provincial nominee program. 25 Ontario hospitals and health centres have used this program to retain specialist doctors and nurses to better provide health services here in our provinces and half of Ontario's universities have used the program to retain world class health services in our province. Mr. Speaker, our government believes that the time has come for Ontario to redefine its shared immigration relationship with Ottawa so we can best position this province for success. Thank you. This week and this month, we are celebrating Small Business Week in Ontario. Small businesses, the heart and soul of job creation are struggling to make ends meet in Ontario. You have already taxed hard-working tradespeople by slapping a new 576% trade tax courtesy of your base street bureaucracy of the College of Trades. Section 7, Minister of the College of Trades Act allows your college of trades to tax employers for membership. Will you stand in the house today and promise employers that they will never have to pay the trade tax by the College of Trades? Mr. Speaker, I'm delighted to respond to that question. In fact, we are very, very clear, Mr. Speaker, some time ago when we waived that provision for employers so that employers are not paying membership. But I don't know why the member would want to confuse them today in almost making them believe that they are. Employers are currently exempt, Mr. Speaker, when it comes to membership for the College of Trades. We did the College of Trades up and running. And Mr. Speaker, they have, indeed, reduced ratios for apprenticeships more than any every government in this legislature on all sides of the house combined over the last 20 years. So, Mr. Speaker, they have made some great progress today. We are confident that they will continue to do that. And we are confident that they will continue to listen very carefully to the business comments. Well, thank you, Minister, and you waived it for one year, 2013. Now, we don't know what's happening after that. Only in Premier Wins, Ontario, which slapping the new trades tax on employers be the best way to celebrate Small Business Week. Meridian Credit Union, Ontario's largest credit union, recently conducted a small business survey with Harris Decima. The survey you found, 75% of your trade tax on employers will further punish these small businesses. The difference is clear. The Ontario PCs on this side of the house stand up for Small Business in Ontario's Main Street. The Liberals on that side of the house stand up for their multi-million-dollar college of trades bureaucracy on Bay Street. Small Business Week is your golden opportunity, once and for all, to confirm that employers will never pay your trades tax. We have to pay your Bay Street trades tax. Thank you. Minister? Rhetoric and fear-mongering aside, we very deliberately did not proclaim Section 7, and the member knows that. We have no intentions of doing so, Mr. Speaker. So we've been clear about that. We've indicated that, and I think that's important. But I suggest the member from time to time, and I think he's already been able to contact the new chair of the College of Trades, David Tabucci, an esteemed former colleague in this house and esteemed former cabinet minister of his party. Mr. Speaker, I'm very confident that Mr. Tabucci is going to do a fantastic job as our chair. I would hope that the member opposite would share that confidence in this fine gentleman, a former colleague of his, who we think is going to do a tremendous job for the trades in the province of Ontario. We're very proud of how far the College of Trades has gone. So far, a lot more work to be done, and we think Mr. Tabucci is just the fella to lead us there. Question? Thank you, Speaker. My questions for the Premier. Last Tuesday I was invited out to the horse races in Fort Erie. It was a bittersweet day for the community, because in spite of the proud Niagara Racing tradition, this Liberal government has decided that the Fort Erie race track doesn't deserve a 117th racing season. What does the Premier have to say to horse people, track workers and the community members about what her government plans to do to shut down horse racing at the Fort Erie race track? Let me say, Mr. Speaker, categorically that that is not true, that I have every confidence that if Fort Erie race track wants to develop a business plan to work with the OLG, they can have a future, Mr. Speaker, but it will be a different future than the present situation. That is the reality. We have said all along that the horse racing industry needed to change, that the slots at race track program was not accountable, was not sustainable. Let me just read what some of the people who are in the horse racing industry have said about our plan, Mr. Speaker. Mr. Ted Clark from Grand River Raceway, it's remarkably better than what our outlook is. We essentially went from a place of having no relationship with government and no support to a place where we now have a spot to make a plan. This provides a new set of building blocks to move forward. We've been given some tools with which to work and hopefully we can put them to good work. Mr. Speaker, the people in the industry see a way forward and we are looking forward to working with them. Thank you. Mr. Speaker, nobody in Fort Erie can understand why the Liberal Party doesn't deserve a viable future in horse racing. Not track CEO Jim T-Bear or Fort Erie Mayor Doug Martin, not the Jockeys or the concession stand workers, not the kitchen staff, the stable workers, maintenance security, the mutual desk operators or the suppliers, not the horse owners, the fans or the bugler who calls out the post time and not the veteran groomer of 36 seasons who pulled me aside and asked me to deliver a simple message to the premier. Will the government see the light and save horse racing at the historic Fort Erie race track? Thank you very much Mr. Speaker. The panel who did an in-depth look at how we could put a sustainable plan in place noted that they urged the government to work with Fort Erie to develop an alternative and sustainable plan. So there is nothing written in stone that says that Fort Erie doesn't have a future Mr. Speaker. I understand the politics of what the leader of the third party is doing right now but it is not responsible of us to suggest that something that has not been accountable has not been transparent which was the slots at race track program should continue. We have got a plan in place and Mr. Speaker I have a copy of the plan here. I can send it over to the leader of the third party because the plan that was in place, the program that was in place was not sustainable. We've put a sustainable plan in place. We look forward to working with Fort Erie so that they can put a new plan in place Mr. Speaker. Thank you Mr. Speaker. My questions for the minister of dementia. In my recent visit at the long-term care facility, both the caregivers and the family expressed concern about dementia. As the minister well aware, statistics shows that three of five people with dementia will go missing some point to time. Sadly statistics also shows that 50% of those who go missing for 24 hours, serious risk of death or injury from exposure of dementia. Can he please explain to the legislature what the government is doing to address this growing concern. Mr. responsible for the seniors. Thank you very much Speaker Maya. My thanks to the member from Scarborough for a very deep understanding and compassion with respect to this very serious issue. Speaker in March of this year, we in partnership with the health and safety awareness program named Finding Your Way Wandering Prevention Program aimed at people with dementia who may go wandering and go missing. As part of this program Speaker, the old time society will distribute kids that include tips and resources to families and caregivers preventing wandering incidents and act quickly in cases of missing seniors. Our mission is to help people with dementia who may go missing and go wandering and go missing. As part of this program, we in partnership with the health and safety awareness program named Finding Your Way Wandering Prevention Program aimed at people with dementia who may go missing and go missing. As part of this program, we in partnership with the health and safety awareness initiative such as the one the minister talked about finding your way wandering prevention program. However, many family members and caregivers are unaware exactly what is in the kit, the finding your way kits assistant preventing wandering enhancement community response when the senior goes missing. Mr Speaker, through you to the minister, can he please elaborate on the content of the program? Mr Speaker, we will have family and caregivers established a plan to ensure the safety independence and dignity of an individual. The kids, by the way, they are available in English, French, Chinese and Punjabi and they include a personal ID page that can be shared with police in an emergency, instructions on what to do when a person with danger can go missing. As well, a list of important tips on what to do when they are reuniting, when reunited after a missing incident. Mr Speaker, on there you can conduct the old summer society, one of the 38 society across our province, two on there, two on one to obtain a kit and as well it's available from downloading it. Mr Speaker, thank you. My question is to the Premier around jobs and the economy and Premier, as you know, the 40 year racetrack is 116 years old. It survived two world wars, it survived the Great Depression but it's not going to survive the McGinty win Liberal government. Premier, I look at everything that's going on, you seem to want to close down the tracks and toss people out of work. Let me be absolutely clear about this. I fought for that track. I fought to keep it open. We gave it a 10 year lease on life and I plan to do it again. I hope we are on the same page on this but let me test that out. Folks in Fort Erie reject this notion of a festival meet, a notion of a small town rural fair is not good enough for me. It's not good in our industry. It's not good enough people of Niagara. Will you commit to a full racing season next year to give some like to this community? Thank you. Premier. So the starting point for this discussion is that the slots at racetrack program was not sustainable. It was not accountable. It's a plan that was put together by the government. It's not an option that was put forward, Mr. Speaker. What I have said is that the government, the Fort Erie needs to work with OLG to come up with an alternative business plan, Mr. Speaker, but to pretend that somehow what was in place was accountable and was sustainable over the long term is just not the case. Hold on a second. That's where I was born and this issue. They signed the deal. Half the job losses are on your back. Thank you. Please finish. I fought for the track. I kept it open. I'm proud of that. I'm going to do it again. We got a plan to do so. I appointed Randy Pettipis as our lead on this issue. He's got a plan. This is the track reporting your own Sidinsky report with the second highest wagering in Ontario and at the same time, your plan is going to road to closure. So let me ask you this. You're the Minister of Agriculture as well as a premier will agree to sit down with ready Pettipis and I to actually give life to that track moving forward and ensure our sustainability. Thank you very much, Mr. Speaker and I have fought to get horse racing on a sustainable footing. Mr. Speaker, I have made. Oh, Mr. Speaker. It's been as almost like a drive by heckling. It's not helpful when I'm trying to get control, but also I will. I know your voices by now and I know who to come to. So I'm asking that it stop and the member from the PN Carlton, please don't shout the Premier down. Thank you. Subject of festival meets Mr. Speaker. I would just remind the leader of the opposition that the Kentucky Derby is a festival meeting. Thank you, Mr. Speaker. To the Minister of Health and Long Term Care. Last week, my constituent West Bland was in news across Ontario because of the road blocks he faced in accessing a doctor ordered pet scan. Mr. Bland was forced to make the long six hour drive to Thunder Bay instead of a much shorter trip to Winnipeg. My office has been in a regular touch with the minister. Can the minister please explain why her office didn't take steps to ensure that Mr. Bland could access the care he needed quickly and close to home despite the minister's knowledge that he was being denied this care. Thank you, Speaker and thank you to the member for the question. I must say I'm a bit surprised at this question because she and I had a very good conversation I thought last week about what the minister was going to say about the care he needed. He was directed to the wrong place for the scan that he needed. Unfortunately, the Winnipeg regional health authority has sent out information to physicians in Manitoba that was not accurate. We've identified the problem and we've corrected that problem. I am absolutely committed as I told you. If the minister is available in Manitoba, then we cover that care speaker. If they can get the care here in Ontario, they will get it in Manitoba. We're taking the appropriate steps to ensure this does not happen again. Thank you, supplementary. Thank you, Speaker. The problem is this. First of all, I need to say I appreciate that the minister did say correct it. Manitoba health continues to insist that Ontario patients will still have to seek prior approval for out-of-province procedures such as PET scans as stated in their memo. The minister has said that she has fixed the problem, but has she really fixed the problem when people will continue to wait weeks for approval for out-of- province PET scans or when they're actually forced to go back? Well, Speaker, I do my best to do my job in the province of Ontario. The best I know my responsibility does not extend to the province of Manitoba. They have set up this rule in Manitoba, Speaker. It is their rule, not our rule. I am committed, as I told the member last week, to do what needs to be done at a ministry to ministry level to provide that system for the patients of northeastern Ontario. As I said earlier, north-western Ontario, they deserve to get the care that someone in Ontario is entitled to, Speaker, and if Manitoba is closer, that's where they get it. So we'll continue to work with the government of Manitoba and the authorities there, Speaker, to make sure that the people in north-western Ontario get the care they need. The second question is for the Minister of Research and Innovation. Ontario's capacity to compete in the global knowledge-based economy depends on our ability to harness our research strengths, encourage innovation and provide support to entrepreneurs. Local business leaders I've met with in Scarborough tell me that Ontario needs to remain a leader in the entrepreneurship to keep our economies strong, and given the challenges in the global economy, it is more important than ever that we take action that helps turn great ideas into thriving companies and new jobs. Speaker, can the minister tell us what action the government is taking to ensure that entrepreneurs are getting the support they need and that programs are easily accessible to them? Thank you, Mr. Speaker. I would like to thank the member for that important question. Mr. Speaker, entrepreneurship and innovation are at the heart of our government's jobs and economy strategy. One of our initiatives is the Ontario network of entrepreneurs made up three networks. First is our 57 small business enterprise centres that are located in municipalities and they help small businesses at the local level. The second one is our network of regional innovation centres which serves to coordinate the work of all actors at the regional level and the third and last one is the business advisory service which provides consultation and mentorship to growth businesses. Mr. Speaker, I am very proud of our government's investments in which supports entrepreneurs and innovators across our province of Ontario. Thank you. Don't the member from Bruce Gray, Owen Sound, on a point of order. Mr. Speaker, just a reminder that the Ontario dental association will be hosting a sports mouth guard fitting clinic in room 340 from 12 to 5 today. It's opened all MPPs and staff and a further reminder that the legislators play their first game of the season this Thursday at 5 p.m. against the firefighters at the Rico Coliseum. Thank you, Mr. Speaker. Thank you to the member from Bruce Gray, Owen Sound, on a point of order. Thank you very much, Mr. Speaker. I would like to welcome Amanda to the program and it's great to have her working in here in Bruce. Thank you. Then I'll do my reminder don't forget the wine tasting is this evening at 5 p.m. Can't forget that. There are no deferred votes. This house stands adjourned until 1 p.m. this afternoon. I think that's the purpose of what we're doing.


Welcome in to the Tracy Johnson show. I'm Joe Wombo, joined now with Tracy Johnson, head coach of the women's ice hockey team and coach. Step one of goals and expectations of the season, making it into the CHC playoff and then winning the first game against Johnson and Wales, two to one. How do you guys feel about that game, first of all? Well, we were prepared all week about putting the puck in the net. And we knew we were facing the goaltender of the year in our conference and that it was likely going to be a close game like it was. And luckily, we did find a way to do that and punched our ticket to the final four. A goaltender of the year on the ice and player of the year on the ice. So there's definitely some fireworks there. And they didn't disappoint at all. They did not. It was a good game all around. I think we are ready to get prepared going into this final weekend. And it's weird that's going to be our last week of practice. But we're doing what we can to keep the energy high and just get ready for a fun weekend. And it definitely is looking up to be a fun weekend. You guys are going to play Endicott on Saturday at 12.30. A team that you guys have played pretty tight all season. What are your, what are the things you're focusing on heading into this game? I think, again, bringing some energy and just being ready to go and focus on what we need to do to play our game. This is a rematch of the championship game last year. And so we know that they're going to come out with a chip on their shoulder and looking for a little bit of revenge. We have to be ready to give them a full 60 minutes of our game. And hoping that it's another good, exciting weekend. You guys got an opportunity to give revenge yourselves, too, for how the games went earlier in the season. Is that any part of your mindset, how those games went to get you prepared for these games? Absolutely. We definitely have to keep that in mind and know that they beat us twice in our house. So I think that's an excellent point where we have to remember that feeling and be ready to go. And that was back in November. And we're a different team, and they're a different team. So excited to see what both teams put on the ice on Saturday. And just to keep reiterating the fact, Chelsea Blackburn play of the year, we've talked about her all the time. But Monica Posick and Natalie Rosendahl also second team all conference. Just having those three on the ice, on line matchups, what does that do in terms of morale for the team? I think it's important to have just great leadership from our entire junior class as a whole. It's a great recognition for the three of them, absolutely. But can't understate what the rest of our team has done to help put them in those positions as well. So hockey is one of the quintessential team sports. And we have certain players that obviously get the attention, but you also need the players that don't necessarily show up in the awards or on the score sheet to be ready to go. You win games with those players. And so we're excited to get just prepared for a full team effort this weekend. That's a very good point to make. Those players do get the recognition, but if they don't get the puck on their stick, it's not going in. They're one of the best finishers and the sisters on the ice. But the rest of the team is doing that for you as well. Absolutely. And we take a lot of pride in trying to play discipline D zone. And D zone is something that doesn't necessarily show up on the stat sheet as much. Obviously with goals against, you can track it that way. But a lot of things that it takes a lot to win. And it's not always just the point production. You need that as well. But again, just really need a full team effort for a full 60 minutes and 65 if need be, or even longer than that. So it's playoff. So you play overtime until it's over. And it's an exciting, exciting time for hockey. Yeah, that's something to remember from last year's championship game. There's over times. I think there were overtime games and almost all of those final three. So hopefully we can avoid that get it done in 60 this year. That's what I'm hoping to. Yeah. Well, Coach, we wish you the best of luck in there. And maybe we're playing on Sunday, bringing home the cup again. Yeah, hope so. Thank you. Good luck, Coach. She's Tracy Johnson. I'm Joe Wamba. This has been the Tracy Johnson Show.


So, this is the standard trick we always use in probability right. If we do not know the underlying distribution, we go with the samples of this distribution and use that to have some empirical estimates of the quantity that we are trying to optimize ok. So, empirical estimate of the quantity we are trying to estimate. Here, this is the quantity if I know, I could go into this optimization right, but I do not know this. So, I want to get the empirical estimate of this using my data samples. So, the standard thing here is to do empirical. So, now, what will be a good empirical estimate of this quantity from the data samples I have? One thing is what I can do is I can say my L SH. So, S is the training data that I have been given. I can use this and I am going to write an empirical estimate for this as 1 upon m 2 ok. Let us understand what is this doing? I have S is given to me, S is given to me what I am doing is and I am trying to compute this quantity for my hypothesis H. So, I will just see on how many points I agree with the value y i, y i is the label right. So, this quantity is just give me this. So, this is the set. So, the value within this braces is going to give me set of all the points, the data points on which my hypothesis H does not agree right. So, y i is the corresponding label of x i, I am just counting how many points my H does not make a correct prediction and now I am dividing it by m ok. So, what is this size? So, I am taking the cardinality here that means, the numerator will tell me the number of points where my hypothesis H has made incorrect predictions and I am dividing it by m. So, what is this quantity is telling? The fraction of the points on which my hypothesis has made a wrong prediction ok. So, next. So, henceforth what I will do is this x i, so x 1, y 1 these are actually one sample right, but instead of right I am just going to write them as capital X and Y. That means, this X is a random variable, Y is also random variable, but this Y depends on X to the function f. So, this X is a random variable which is drawn from my distribution D. Once I note this, this Y is simply the function f of that point X. So, these are my points like I have this is my random variable and these are just like realizations of this ok. Now, suppose this is a particular realization, but let us say let me say that my I could have x 1, y 1, x 2, y 2, x and y. This could be all of them drawn from the same distribution right. So, this X, I, Y, I coming from the same environment. So, these are just m points drawn from the same environment. Now, if I say that these points are drawn independently and anyway they are identically distributed as m cost infinity what you what this quantity is equal to. So, if this quantity is going to be equal to this the probability of the disagreement, why is that which what did you what is what did you apply to conclude this. So, if this Xi pairs are IIDs independent identically distributed I can apply my large left number says that this has to be equals to this right, but it is just that m is not infinity here, m is some finite number that is why we are going to call it empirical risk. And now this quantity here we are going to use it as a proxy for this quantity and now I am going to minimize this over h ok that is why we are going to call this method a empirical risk minimization.  So, this has in general optimally just we are going to call it a ERM. ERM technique what it is going to do is as minimize over h belong to h now do. I am trying to my goal was to minimize this, but it is just that I do not know this, but what I did is I found a proxy for it based on the quantities I know and then trying to minimize this quantity ok. Next the question is fine if you do like this whatever this quantity is the minimum value of this if you do this how far these two quantities are away from are they very close to each other or they will be very far from each other. Your goal was to minimize this right, but you ended up minimizing this. Then you would like to ask the question whatever I got get from doing this how far this value is going to be from this value ok. And whatever the hypothesis I get from this let me call this as arg max of this the hypothesis I am going to get I am going to call it as ERS and this hypothesis. So, notice that it depends on the training set you got and over the hypothesis class you are trying to find your hypothesis ok. So, this is one training set that I have given to you from which you got your empirical risk minimization hypothesis. If I change this S can your empirical risk minimization hypothesis can change it can potentially change right. Because these quantities have been explicitly used all these data points have been used coming from set S if you are going to say it S it is going to change ok or maybe like I will instead of this I will also I will also going to use it as HS simply this quantity this empirical risk minimization. So, subscript S denotes makes it explicit that this hypothesis depends on your training data ok. So, now, your training data whatever that is given to you it is generated from this particular distribution D right every time you are going to generate this data you may end up with different set of data points ok. Because of this this set S S itself is a random quantity ok and because of this this H of S can be also random right it depends on the data set you have used to generate to learn this hypothesis. So, yes this H of S is a random quantity depends on the data set, but as I said what kind of guarantee we can give about the hypothesis we got by doing this empirical risk minimization with respect to whatever the best one ok. So, there is when we do all these things the hypothesis class matters if you are going to change hypothesis class things can also change. What we are going to now just to understand what we wanted to see like the difference between this minimum and this minimum let us focus on the case where we have only hypothesis class which has only finitely many elements in this ok. Before that how many of you know what is overfitting? So, what happens in overfitting? No just tell me what happens on the training data? So, what will be this quantity let us say if you have a very low if you do if you have overfit what is this quantity for some hypothesis you can always find a hypothesis which will ensure that on your data points it exactly does the correct job. If it does the correctly job this quantity is going to be 0 right. It may do a very good on the training one, but when I look at the actually the test error here where the points are not just these points right the data point they could be also coming from other parts it may not do well.  So, for that like that is not of an interest. So, we will not go more into that, but what we are going to assume is this hypothesis class is finite size that is the cardinality of this set is finite ok. So, if this hypothesis has like infinitely many components in this right you will always come up with the hypothesis class which will overfit and make this loss 0 right and in that case you will your empirical risk minimization always end up showing you a hypothesis class which is like a overfit on the data. So, when you have only finitely some you restrict your hypothesis class that kind of overfitting you may avoid. So, let us for time being assume that this hypothesis class is as a finite element in this ok. Now, let us say whatever hypothesis you got from your training data I want to now measure its performance. So, what I when I will then how I am going to do this? So, here the H that has been you have found out is your H of S based on your training data right. Now you want to see what is its success. So, what you will do is then whatever H of S you have got now I want to I am interested in this quantity this is. So, you have you have done this empirical risk minimization during data set and you have come up with this hypothesis H of S. Now, I want to measure its performance. Now, I would say your empirical risk minimization has given you a good hypothesis if I can show that this quantity is small right or like if this quantity is 0 that is the best maybe like, but I want to can I claim that this quantity is going to be small. So, what are the things that governs how good your hypothesis H of S? So, what do you think? What do you think? You will have come up with a better hypothesis H of S that will make this quantity smaller. When you think what are the things in your setup that are going to affect how good my hypothesis H of S? So, I am assuming that this data points are generated in an IID fashion right. So, instead of giving let us say let us take m equals to 10 let us say I just give you 10 points and then using those 10 points you convert your empirical risk minimizer let us call that as a H S 1 there and later I give you 100 points I added 10 more 90 more points to your 10 points you have 100 points and using this 100 points you come up with this another H S 2. What do you think? H S 1 will be better or H S 2 will be better? Why? So, when you have larger so, you will be approximating this function more accurately and maybe because of that you will end up with this. So, naturally m has a role to play here right how many data points you have on what how good this H of S is going to be. So, notice that like there is also I said this could have m points, but each of the points here itself could be generated independently right. So, let us for time being let us say that let us take a two dimensional case let us say my x axis denotes humidity levels ok and my y axis denotes. So, instead of this let me call it x 1 component and x 2 component denotes my humidity levels sorry temperature levels and let us say these are the points. So, these are some points I have observed let us say when it rains when high humidity and high temperature when it is going to rain high humidity low temperature ok let us let us assume we are like some weather fake weather experts I do not know what a let us say in this region it is going to rain all these points has the label that they are going to rain and below these points these are like not going to rain yeah I am just like this is a hypothetical case it is not necessary there should be a nice separation like that it could be much more complicated. And like ok so, these are data points, but let us say so, this let us say this this is my range of humidity let us say humidity goes from some value 0 to maximum some value let us call this x. So, this is like x 1 max and my temperature also 0 to let us say some x 2 max something like this ok. Let us say the true the true like let us say whether the true in the nature the actual way it happens is whenever let us say in some fashion. So, in this let us say it is all going to rain and in this it is not going to rain. This is how let us say the actual environment behaves. Now, what you are doing is you are basically getting samples from this right over the past history you are basically getting. So, this is rain and this is no rain.  So, it means there was not enough rain in those cases. So, because of that most of the data you collected happens to be from this portion from the last 10 years where data set will have data mostly coming from this portion ok. If you are going to train on this portion of the data do you think your the hypothesis you are going to end up will have a we will do a good performance no right because it did not get to see the full things here like it did not get the full picture. So, it may not be able to do. So, and also like if it. So, if you just see this what what it will feel that ok it looks like this in this part of the world it is always going to be draw every year it is going to declare that it is going to be draw draw draw and everybody will panic. But let us say if all the data point like last 10 years happens to be again like flooding or something and you got lot of points from this. This is also going to be bad whatever you are going to get it is going to predict it is going to rain rain rain and it is not going to be a good thing. So, which from which portion of your distribution that data cams also matters right because of that the S itself is going to matter how good or bad your hypothesis that is why we have also substituted it. Notice that we have saying that this points are IID generated right. When I am and I am saying this points are getting IID. So, when I am saying this IID generated it is unlikely that all the points are sampled they concentrate on one area to get this. So, maybe when I am generating IID maybe possibly they will be spread more in this and maybe they will give me a true representation of what is happening. But still when you are generating IID with some small probability you may still get samples only from one region of this right. It is not like even if you generate IID you will get with high probability samples from all over the region and the probability 1. It may end up with some small probability you it may happen all the data points you generated could be coming from this small region which could be bad representation of this. Because of this whatever I have here this quantity here itself will be determined by the data samples I am going to see and not only that what is the size of that data set. You may have large samples you could increase m to large number of points but with some small probability you all of them might have come from a small region small area which could make your empirical risk hypothesis really bad because of that this value could be also bad. So, in this case we want to see that whatever this hypothesis we learn from this given data set S what kind of guarantee I can give on this. So, is it true that if I have this large number of points in S that is enough to make it arbitrarily small need not right because as I said you may have large number of points but those sample points might be coming from some small region would could make this a bad representation of your space ok. So, the kind of guarantee we are going to give henceforth that is why depends a probabilistic guarantee we are going to give and we will only going to say that how small this is going to be ok. So, before we give any such things we when to make such reasons concrete we may require some assumption I will just tell you what I mean. We are going to assume that there exists a hypothesis in my hypothesis class such that it is going to give me 0 loss on all possible realizations of my data set. So, let me make it formal. So, with this assumption we are going to call it as real life ok. So, we will assume that there exist a hypothesis class H star in my hypothesis class H such that whatever this quantity I have whatever the prediction error I am going to get. So, what does this imply? We are basically saying that S star equals to f with probability 1 ok. So, it may happen that on some points it may this H star may not assign a same level of f, but those number of points are 0 mass. So, let us say this assumption holds ok. If let us say if this assumption holds is it true that if I compute this quantity for any S on H star what will this value be that will be also 0 right. So, so this basically means that you take any data samples I will have an H that will have a 0 loss ok. Now, I assume that there exists such a H star which is belonging to my hypothesis class. If I go and do this empirical minimization whatever that minimizes this value. So, we know that at least there is one H star here that is going to make this quantity 0 right. Whatever H S we are going to have that is going to have this quantity to be 0 and there could be more than one, but what we are interested is the one which minimizes this ok. So, let us assume this this can be all easily realized, but for time being let us say that my hypothesis class is expressive enough such that it captures the true labeling phenomena. That means the true label it is it can do as good job as a true labeler that is it can be as good as a the true labeler labeling function f that is why we are saying. So, if this happens then we have the following result. So, you have to get used to such the statements now onwards. So, let us try to understand what is this result saying ok. It says that let us say H B a hypothesis class where H S finite and a delta is given to you and epsilon also given to you. Then if you are going to choose your m, m here is going to denote the number of data points to be larger than this and if you are going to give me a data points which are generated IID and it has at least this m number of points in it then whatever this error whatever the hypothesis class I am going to learn by empirical risk minimization it is guaranteed to have a loss which is smaller than epsilon and that is going to happen with probability 1 minus delta. As I said I cannot give a deterministic guarantee on this because even though I can give a lot of samples the samples may come from some bad region. So, I have to I can make this guarantee I can only give a probability guarantee. Now let us let us try to understand how to interpret this result. I have let us say I you are in a company you have been told to find give me a hypothesis whose value is going to whose true value this quantity is going to be less than epsilon with probability 1 minus delta. So, let us say your boss has given this parameter to you we cannot guarantee anything in word with probability 1 right in being realistically we can guarantee something to happen with some probability maybe that probability is very high like me being alive tomorrow very high, but it is still probabilistic right there is always some maybe there is also some case that probability that sun may not raise tomorrow is not with probability 0 it may not raise some with some positive probability. So, we have to give similar like so I am let us say I am also asking the same thing keeping that in mind I will ask give me this guarantee with this probability and my guarantee has been specified by two things I want loss to be not more than epsilon it should be less than epsilon and this should happen with this probability 1 minus delta yeah this delta yeah we will be careful with delta and it. So, these are the parameter that has been given to you if anybody ask you to guarantee anything you also cannot give him that guarantee right you will be also demanding you are going to tell see ok I will guarantee you this, but you give me this many data points m number of data points and how is this m determined like this. If you are asking for epsilon accuracy epsilon guarantee and with delta accuracy I want you to give me this many samples then I will guarantee you that whatever the hypothesis I am going to give that will have a loss which is less than epsilon ok. So, if somebody ask you get me this job then in 1 hour or something then you will ask give me 10 GPUs then servers I will get it done in 1 hour. So, like this somebody is asking you to give you this guarantee then we are going to say if you give me this many data points then you will be guaranteed you are guaranteed ok. So, you see this. So, this is a kind of wanted to go through quickly this supervised setting like all of you my who have done this course in machine learning when you touch upon this learning theory this is what you are going to do there right. So, this is kind of this is touching upon the sample complexity. If you want to learn something with some guarantee you need certain number of data samples ok. So, this kind of results lead to sample complexity result. Now, but this is not our interest right this is just like a precursor what we are interested is I do not have a priori access to this m data points that are given like in this case you have already been given m data points you train on this and try to apply it on a new point and you are trying to guarantee that how well you are going to perform on the new data point right and you have been guaranteeing such things. Now, I am going to say I do not have luxury of collecting all this data right. Suppose let us say in the weather case right like somebody was collecting data for the last 50 years and they give it to you and he is asking you to predict even that we do not do well right like we have so much of historical data, but our weather forecasts are always wrong. But what so that is one case fine, but what it may be happen right like what happens if you do not have any such information at all, but you want to make a good prediction right from day one how you are going going to go about it fine on day one you have nothing you cannot do anything, but after doing something on day one you have some information for day two right. Can you think of doing something better than what you did on day one and you do it is something on day two. Now for the day three you have information about day one and day two can you use this to do something better than in day three than what you did in day one and day two and as information gets to you can you quickly try to do what is the best you could have done. So, that is where we were going to get into this online machine learning here. So, in this case we have already bunched out data we want to train and guarantee what we are going to do from the whatever we learned from the past, but in my online setting I do not have this luxury, but we are going to be ambitious and we are going to set our goal as I want to do quickly as soon as possible. And you will also see that we are going to set our goal as what we are doing is it how good it is compared to the case when I knew everything like I am the oracle if I am the oracle of like nature myself. So, when I say nature it is like about the data generating process if I knew everything I know what is the best I could have done right now I am going to always compare myself to that like I do not know anything I am started getting this incremental observations using that how quickly I am going to do as if I knew everything if you could do it as if you knew everything that means basically you have learnt and now the question is how to set up this and how to characterize all these things. So, that is what we are going to start looking it from the next class and there we are going to see various settings ok. So, let us stop here.


Hey guys, this is rich here on behalf of rich TV live, and we are like getting so close We are 33 days eight hours 32 minutes and 45 seconds away from history And today the whole market like there was mostly red like the red is see right. It's crazy, right? But even in the sea of red in the slaughterfest, which is pretty much everything that we're looking at There are still some big winners MTL o Ni o KALY all up massive MTL o up 152 percent Ni o up 69 percent brand new IPO the next Chinese Tesla. They call it Cali up 33 percent and then there's till ray now till ray is the one that I want to focus on today till ray now at a $119.76 up 14% on all the indicators here on investing comm look at this on the monthly it's a buy on the weekly It's a buy the daily it's a buy and a strong buy and all the indicators are showing lots of strength So what is with till ray? Why are they so powerful? Well, they have thousands of patients already and they have some great products, so This is a company that is on the rise. You definitely want to keep your eye on it I talked about it when they were brand new IPO. I told you guys about it all the way back here actually Look at this. We can go all the way back when I brought it to you guys when they first did their IPO all the way back here Look at this $21 and today at a hundred and nineteen Representing a profit of over five hundred percent. It is incredible now till ray is A pharmaceutical company it develops cannabis based medicines drugs drops and oil products till ray ink is based in Anima Canada, which is in Vancouver, British Columbia. You could see it's a moderate buy now. It's super high I would be very careful up 399% in the last month alone it is on fire This is a company that is a force to be reckoned with it is the hottest IPO of 2018 for sure it is the highest price cannabis stock that has come out over the last few years it is Incredible at a hundred nineteen is showing no weakness whatsoever now I want to show you this till ray does have revenue. They generated 9.7 million for the last quarter pretty good You can see there's some that are higher Charlotte's web is at 17 million green thumb industries 13 million Cush holdings at 12 million CV sciences at 12 million Teratek at 7 million med men at 7 million grow generation 7 million and till rate 9.7 Those are the Canadian companies now. Those are the US. These are the Canadian You can see Kennedy be growth at 25 million for the quarter Aurora at 16, but we know this is going to go way higher and MPX at 14.5, which is massive for MPX, which is currently less than a dollar APH aphria at 12.1 million and I so do y'all which just lifted their halt today at 9.2 million Now you can find everything you need a rich TV live comm hover over stocks all the tools you need Breaking news Everything you need in the cryptocurrency world all the tools you need and it's all brought to you by YouTube You can find our YouTube channel by just clicking on YouTube Bam our YouTube channel will show up and we'll be right there. So follow all the links on rich TV live and There's some news that I have to read to you Which I thought it was kind of entertaining regarding till ray once again at a hundred nineteen dollars today just Absolutely on fire. So of course, you know, we've got a hot till ray and Let's just talk about this news that came out yesterday. So this is a news from yesterday on yahoo It was actually written by Steven Gil foley so he says Till ray gained 9.5% on the session Think that's something the stock traded at a low of 20 dollars on the day that trading opened on the nasdaq market site in july Did you get some of that day? No, me neither. Either did I I'm not going to deny it The shares are now less than two months later 368 higher peaking at a hundred and eight dollars. They're even higher today now at a hundred and nineteen There is no denying the obvious consumer demand. There is no denying legal trends Recreational pot usage goes legal in canada on october 17th And despite the illegal status of marijuana usage in the united states at the federal level More and more states are legalizing the usage of this drug for both medical and recreational usage every year In fact, I am willing to go out on a limb here and say that not only state that has not One state has legalized pot has ever thought about going the other way on the decision Of course not. It's a money machine. It's a cash cow Remember the dog days of august andrew left of citron research does on august 15th left Was bullish on the name with a 45 dollar price target Nearly a hundred percent premium at the time in place The shares would leave the target price in the dust within two weeks I first noticed left bearish on the tillray in early september amid yesterday's pop He reiterated that call citron research expects not only the existing pipeline of cannabis related IPOs To draw investor dollars away from tillray But citron expects that the firm itself will be forced to go back to the secondary market In order to fund its own plans for expansion Really I doubt that Tillray is absolutely on fire Obviously rich tv live is strictly for education entertainment purposes guys Always do your due diligence always do your research before you invest in anything that we talk about here are rich tv live It's a strong buy strong buy strong buy strong buy Congratulations for all the members that won on tillray on a day where almost everything is read Tillray is a huge winner Staying strong not letting anybody not even andrew left short it down Congratulations to all the winners They are a company that has real products real revenue and it's really trading at 119 dollars Do I think this continue? Do I think this can continue? Probably not nothing can go up like this forever, but it's nice to see Okay, there's my opinion on that if you want on it Congratulations, if you got in at 20 dollars and it's at 120 You definitely should be thinking about selling at some point in the green Um, they're most likely will be a pullback at some time, but who knows comment on the video Share it everywhere. Please remember if I win and you win we all win This is your boy rich if you're not winning you're not watching I'm out We are 33 days eight hours 25 minutes and 28 seconds away from history. It's true Tillray will this continue comment down below. I want to know do you think this will continue? It's crazy It can't continue, right? I mean nothing can just keep going up like this, right? It's crazy. Look at that chair thing of beauty my goodness peace


Yeah, thanks for joining us today, everybody. I'm going to present the MetaPyPEX framework today, which is framework for data analysis and termination for multi-lab replications of experimental designs. This will be more of a brief introduction on how we arrived at the framework, what it is, and how we'd like to see being used. And for a bit more details on how to actually use it, please feel free to attend our tutorial on Friday at this year's SMART content as well. So where did it start? We were going to re-analyze data from large-scale direct replication projects like the MenLabs or the multi-lab registered replication reports. And we intended to use participant or item-level data, and we needed that data to be cleaned in order to compare re-analyses with already-published results. That turned out to be much more difficult than we anticipated. But before I'm going to talk about the difficulties, I just want to get some vocabulary out of the way to make sure that we're talking about the same things. So this graphic here represents the basic structure of multi-labs. And when I say multi-labs, as I just said, I mean the multi-lab registered replication reports on MenLabs. And all of these have a very similar structure on some level. And the first interpretable data would usually be item-level data, where each participant is a row, and each item is still represented as a column. And for individual participant data, these rows are still participants, but now the dependent variable has been aggregated to a single numerical value. And these, again, are aggregated to achieve replication-level statistics like between group effect sizes or group variances. And then those replication statistics are used to run meta-analyses to aggregate data for each replication project. And finally, a multi-lab then might span multiple of these replication projects. Yeah, but despite the very similar structure, the solutions they found to document and analyze their data were rather unique. So just a few examples here. The software and users usually are, but sometimes SPSS or other software, the code structure itself was very unique to each multi-lab. So when or by whose data aggregated, sometimes these steps were taken by the replication sites and we don't find the actual raw data. And sometimes that was done at the replication project level. Yeah, the data files themselves are very different. Sometimes CSV files, SPSS files, Excel files, R data, et cetera. And if you include the files with information for the data transformations, so like information that the code sources, the analysis or data transformation code sources, you will also find solutions like text files or Google documents and probably some more. Yeah, so the variation across the multi-labs is quite large. There's little consistency in naming conventions, sometimes the verbal descriptions and other provided details on the data transformations are sparse or even inconsistent. Some of the code solutions are really complex, though interesting. And sometimes we do not find cleaned data sets at different levels of aggregation. So this just results in a lot of detective work for anyone who wants to reuse that data and makes computation reproducibility much harder to achieve and actually check. Yeah, and I want to elaborate a bit more about computation reproducibility. But that would mean you can run the original code on the original data and achieve the same results as reported by the projects. And there were a few great analyses on registered reports and publications with open data badges over the last couple of years. But the results are somewhat devastating to be honest, which maybe just means it's maybe a lot harder to get there than we think about, than we think. So some of the results were just only about 30% of the articles these projects looked at were actually reproducible. The computation reproducibility depends on the skill level of the analyst, which then again poses the question like how much skill is necessary until it's not computational or reproducible anymore. Most of these analyses agreed that using non-proprietary formats helps a lot and providing version control. So that could be using solutions like RN, but also using containers and like Docker, for example, and also just simple stuff like using relative locations. So you have to change less file paths just when you're trying to rerun it. And some of these were already implemented, some of these best practices were already implemented in some of the multi-labs. So for example, many labs too found a package solution for their data transformations. I think the package at the moment could be pulled, so I'm sure if it's available right now. There were container solutions, a lot of non-proprietary software was used, and also bug trackers, which are great just to make sure that the community interacting with those projects is visible and just so we know where people have found errors or deviations. Yeah, but this is very inconsistent across these projects. So our solution to these complications is MetaPipe X. And just to break down the name quickly, it's a pipeline from meta-analyses of experimental data. And these make up more than 50% of the currently published director application multi-labs. And yes, the framework consists of three components. We see on the left the standardized analysis pipeline, which provides guidance to make the analytical structure more explicit and reduces documentation effort. We also created an R package that matches this pipeline, so it analyzes data. It creates standardized documentation for the data at different levels of aggregation. And the third component of the framework is the Shiny app, which we can explore data, which we can use to explore data, MetaPipe X data. That's a combination of replication results and meta-analytical results. And basically it's just a GI to select and visualize multi-lab analyses. So you can also run the analyses within the Shiny app and combine different data formats. It takes SPSS data, R data and CSV files. So you don't have to be able to work with R to implement the pipeline. You can just use this GI. And the most comfortable version to apply the pipeline is the full pipeline function, which just takes individual participant data as an input, which is depicted on the left. And yeah, then just runs the analysis and creates a full documentation of the standardized pipeline. On the right, you see the full structure that is exported by the function. And in R, this is also provided to you as a nested list. With each folder, you always have the data file and according code books, so you can make sense of the columns and the data set. And finally, what we hope MetapyBx may do, we hope it will reduce effort in analysis and documentation. We hope it makes your multi-lab data more explorable, so no matter if it's your own data or you combined or simulated data. And we hope this fosters interaction between the research community and these types of project. Best case scenario, it helps to make the multi-lab format more accessible to primary researchers and students alike and it helps to develop and ask more meta-scientific questions, chat more a light on questions around heterogeneity. Yeah, and that just adds to the meta-scientific toolkit. Yeah, that's it from us, or for me today. Thank you for your attention and please feel free to join our as Macon tutorial on Friday.


Acute appendicitis, AA, is a common cause of abdominal pain requiring surgery, with approximately 20% of cases involving complications such as gangrene or perforation. Diagnosis can be difficult and requires evaluation of clinical signs, laboratory index and imaging. Surgery is the best option for complicated AA, while laparoscopic treatment is recommended for uncomplicated cases. Postoperative antibiotic treatment is only necessary for patients with complicated AA. This article was authored by Eleonora Guaitoli, Guy Tomogallo, Eleonora Cardone and others.