So hello everybody, my name is Don Gooding or as I joke to people tonight I am Mr. Kate Gooding. Both Kate and I work with entrepreneurs. Kate, as you know, has been working with the younger entrepreneurs and I run the main center for entrepreneurial development and some of the entrepreneurs that I've been helping have actually, they're here tonight. So it's a pleasure to have all of you together as a community to celebrate the great accomplishments of all of these kids. So let's just start off with the first round of applause for all of these kids who have done an amazing job. So for those of you who don't know, the Build-A-Biz program has been around in one form or another for the last four years. It started off about four years ago when Kate and I were looking at a variety of entrepreneurial things to do in Maine and she came across this thing called a lemonade day and she said, okay Don, you're on your own. I'm going to go work with the kids. Yes, I did. It seems like it was only yesterday that I was sitting down with yellow, light green and stacey half full and it was actually five years ago and here we are today. So for the first two years, Kate followed the lemonade day national formula and kids were building lemonade stands all over Maine but she heard from the parents and the kids that they wanted to do more and so Kate being an entrepreneur herself came up with this idea that we now call Build-A-Biz. So she gathered together with her board of directors and she worked with some great resources to develop some basic curriculum to help kids get that start to take the beginnings of an idea and turn it into a business and it has been growing over these last two years and you're seeing the fruits of the results that these kids they really look excited when they are talking about their businesses. Because it's not just any old lemonade stand, it's their idea which is really a great thing. So over those years they participated not only in the local statewide business Build-A-Biz programs but also in global, national and Maine entrepreneurship week. And one of the things we did was we actually took the program and instead of having just a physical book we put it online so the kids and parents and coaches have access to it 24 seven either by phone or on computer and that has been we've been able to reach reach right you know a lot further out into rural Maine which is what we were looking to do and even though all of the kids aren't able to come and join us as far as you know we would like them to you know we are slowly growing that out there which is what you know we want to do and so that's you know that's been important for me too and the things that we have added in the last two years what we've been able to do this and thanks mostly to Rob Aldachi is where we've had the elevator pitch competition and here Rob say hi yeah yes thank you and thank you to channel five for filming it and so everybody else can see it so thank you very much Brian yeah just so community television network is the public access network here in Portland and so for those of you who don't really understand what's going on you're being filmed and this is going to be aired on that public access television network so if you want to see this make sure you watch ctn five and in addition next week uh Tuesday the show that is featuring the winner of this year's build a bit is competition is going to start airing so it's really pretty exciting and so that's a good segue into I want to introduce the last year's winners who is here miss Olivia Dan boys can you come wave and turn around say hi to everybody thank you so much for coming you are our first winner and we are going to follow you through your progress and we cannot tell you what she is working on because she is working on a pattern with attorneys down in uh Boston and also with Hugh with the UMO manufacturing system up in 4 and 0 so you'll keep us posted and so with that I'm actually gonna we're gonna talk about the this year's finalist and winners so the first winner raya morrow can you come forward tell us a little bit about your pat pouch okay well my invention and but my business is called the pat pouch which is the pet aroma therapy pouch and this product is like it's a tea bag that you use in a tart warmer and um when you put this tea the tart warmer in a place where dogs will be staying while you're gone and with this product you can provide your dogs with separation anxiety it's a mental disease that a lot of dogs in America have and by using my product you can prevent them from getting this mental disease and I didn't know dogs have anxiety so we have two anxiety winners today incidentally second place was omg anxiety with anxiety and self-conscious problems and ocd and it's um mainly for um littler kids who don't enjoy therapy as much as older kids um do and um it is built with strategies filtered through games so that little kids understand it more and it's you know more fun so um it really sticks with them when they play it and I've gone on a lot of other websites that um are supposed to do this and um most of them were created by adults so not all of them were very kid friendly and um so this one is by kids who have anxiety and those problems so they know what it's like and are going to fix that and how old are you and 10 years old and you're writing this program yes I am and just as an illustration of the small community of Maine where dad Dan Kaloski is actually a mentor in the top gun entrepreneurship program that I run so it all it all kind of flows together unbelievable and then our other two finalists that pitched I mean the judges had a really hard time speaking of judges where is Jennifer there she is so the small business development center give up their time each year to go through the plethora of uh applications and I mean I go through them first make sure they're complete so they don't get hundreds of them uh and then what we have decided is that the video they are able to understand the kids a lot more so for the competition next year they have to have videos for the Bangor uh elevator pitch competition so be aware kids that's what it's going to be for next year so so thank you for yes I'm I guess I'm giving you your job for next year so next okay hailey our our third finalist the company is called gold elephant and the product that I sell is the lip savvy set this set is a three-step system the system is a lip scrub a lip balm and a lip balm and the lip balm is a lip balm with some protection and each of these products can be replaced once you have run out and all the set comes in a little pouch all right and I try tried some and don't my lips look like a couple mentors here they're talking with hailey today so we're trying so hard to help these kids further along with their ideas so if anybody else has any ideas let's help them along and so our fourth finalist there she is Caitlyn Reiner can you want to come up here each of these four kids are actually tapping into some things that we all need hello um whoa my business is called errands for the elderly and it's a business completely run by teenagers we provide services to the older community at very affordable prices and I think it's not just about the services it's more about bridging the generation gap and creating bonds I think that matters a lot as well so yeah that's great and hopefully by elderly she doesn't mean me some days I feel more elderly than others so at this uh at this point actually I'm gonna switch um I'd like to take this opportunity to thank some of the partner organizations that have helped make this happen although Cait does an amazing amount of work she really relies on a lot of partner organizations to reach out to kids and help really make the education happen so we want to recognize a few of them uh Karen Seymour I don't know whether she's here tonight but she was instrumental at the Portland rec department in bringing Bill to this to the kids there uh Kristen Marsh who's the program director of the Portland Boys and Girls Club she's been involved for the last two years and it really does an amazing job is she here yes Cindy Ripley and Melissa Cormier of Waterville Boys and Girls Club they they got into the program this year they really went full steam ahead and did a lot with the the kids I don't know whether they made it here another important partner uh town square media Mike Marcello where are you here okay so um they have radio stations all across Maine and because they kind of took uh Molly and Emma under their wing and put them on the radio fill the biz as a result got volunteers uh recognition grammar lessons and registration it was really great so thank you for all of your help there part of Bitterford uh Delilah Pupori uh we'll be here later she actually went out and she was so inspired by the program she visited three different schools she gave four different classes in the Bitterford-Saco and Rundle area and really helped get kids inspired there um we did mention uh Rob Baldacci uh The Pitch Me Show and Jennifer Sherwood at Maine Small Business Development Centers who really have been they've been uh contributing as judges for all four years the Maine Mall has also been a major partner by allowing registration events uh at the Maine Mall so they've been really instrumental in getting the word out uh and then finally also important I think they they had to go off and work but they the students at USM's SIFE and then now Anactus program which is a really active student service entrepreneurship program there they've developed videos for the curriculum that they developed this year a really cool entrepreneur game do we have that on display yeah in the back right in the back so if you you know want to play entrepreneur that's a game that they've actually developed as as part of the overall program so that's really kind of fun also want to take this opportunity uh as a non-profit there's a board of directors that has contributed a lot uh Steve Wallace uh who's the chair he's done a great job leading the charge and he'll be doing that as the organization cars out in the future according to what the parents and the kids are asking for uh Stacey Haskell of Bangor Savings Bank she's not here tonight but she's the vice chair and absolutely a huge supporter in getting the funding to support these important programs over the last four years also a huge thanks to Lisa Panette Lisa I see you wave the back there when she joined the board uh she she told Kate Kate uh and Lisa go back a long ways back to Jackman and uh she said well I don't know how to support a non-profit board of directors but she's been a huge help excuse me uh Kevin Brunel treasurer are you here Kevin yes thank you um Michelle New York who is at Southern Main Community College uh the entrepreneur guru there uh Kyle Kirby a lawyer at Pierce Atwood and an entrepreneur enthusiast is Kyle here yes thank you Kyle Tom Leonard a Chinbo project manager and a long time friend of Kate yeah Tom's in the back there Angie Hilton who owns her own media company Northeast Media she's a really great at it Angie yes despite being uh having that big boot on her and also just want to give special recognition until Jill Barkley I know she had to get ready to run off but I don't know that she's still here but she was executive director for about eight months during the past year um then finally it's also important to recognize sponsors uh non-profits depend on sponsor uh sponsors who get their funding uh because unfortunately there is no state funding for uh kid entrepreneurship um there are I think something like 25 different sponsors a whole bunch uh gave in kind and cash I'm only gonna uh have time to read the names of a few so Main Technology Institute Pierce Atwood Balduchian Business ProSearch Main and Company Town Square Media Portland GWY Oxford Networks and finally saving the most important for last Bangor Savings Bank uh I can't emphasize how important that their support has been to help Kate keep going um with you know doing a startup when it's a regular business is hard doing a non-profit startup is amazingly hard and Bangor Savings Bank support has really been critical for that so thank you sponsors and I'd like to recognize kids now are for their kidpreneur stories and Main and Company has been working with me for a few years in support of that and we didn't let this out this year because I wanted it to be a surprise so the kidpreneurs were here and they don't know it so first place kidpreneur story this year they they're unique they touch your soul they have passion and the two top winners this year first place goes to Caitlyn Rainer and the second little cute story goes to North and Nibbles Mike can I get to come up here Mike Morrison so we have uh a special a couple of special awards here what are we gonna call this we're gonna what are we gonna call this we're gonna go this new uh Main's radio new voice award to Molly and Emma Carlton they can join the morning have a cute morning show tomorrow anybody hear the radio show of the radio commercial that they did it was amazing and Molly come here and Molly gets another prize for the best lemonade stand she has been doing it for four years that every year she adds on something new and two years ago when it was pouring she added on a drive-thru where her dad stood out there with an umbrella and there's one more there is so oh why I still have a couple more oh you do have a couple more okay well how don't you do though they're not on this list okay where's tree super cool car washing he's raising money he raised more than enough money to adopt a seal actually for Melissa and Cindy because you girls did such an amazing job jumping into this this year I get up there to meet them and I look in the back garden they're doing all this like shuffling back and forth he made this huge banner welcome Kate build a business all right so where are those black hole brownie kids yum come here Samantha just because I know you like to give me a hug preventing Kate's trailblazer where are those PBJ great job you're welcome gonna hug no okay that's okay Holly and Emma you're just gonna go home with lots of stuff cake loves gifts last one that's not on the list is yeah this person just it just brings tears in my eyes she always just goes above and beyond and I just I you know it's not I can't do enough for her so would you come up here Lisa Panette get through this without we have a lot of mental nervous support all of these things get done with a huge team of people but there's always somebody at the head who maybe doesn't get enough thanks and so as Mr. Kate today I wanted to make sure that opportunity was not missed um I don't know if I can do this without breaking up here but um many of you may not know that over the four years that Kate's been doing this she's had she showed a great deal of the entrepreneurial grit that it takes to be successful grid is that character that when things get tough you keep going to help make things happen and she's had three back operations and the replacement and she's been suffering from daily extreme migraines for the last five months and yet she's kept on making this program the success it is today so I just wanted to give an opportunity for all the kids and who all the other people have been part of enough a part of this great program to say thank you to Kate so thank you everybody I couldn't have done it without all of you and all I and all I can say is we're going to be bigger next year right spread the word


I just want to make two points that I knew that Rene or Johannes will be in the format. So I decided to not make a general introduction to the area because, as you heard, he made a wonderful introduction. So it's a bit cheeky that I used. I'm thinking about what Johannes said. And the second thing which I want to mention is that we had to submit the abstracts and the titles as you know, ages ago. And I changed my mind since then. So I'm not going to talk exactly about what you're seeing here. And the other two authors are also here. So I developed further from what I submitted in the abstract. So I'll start with two images. And you've seen a lot of this. And this is the site of Nebelivka, which is about 20 kilometers to the south of what Johannes just showed you. And as he pointed out, there will be a regular planning. And as you can see, this is a very regular.  Rather, you will see that there are some variations. But in general, you don't need degree in archaeology to see that this is actually something which is very regular, very planned. Something made quite an effort to do that. It's not something that grow out of nothing. There is something which serious planning went off. So the size of Nebelivka is 238 hectares. And it is on the basis of about 90 radiocarbon dates. It dates to the early part of the fourth millennium BC. And this one is a geophysicist interpretation plan of the geophysical plan. And not to see the red things here are actually houses, structures, dwellings, whatever you want burned. Therefore, they're in red. Well, the other color, we are not quite sure. We have almost 1,500 of them, right? So to build these, we need about 67 hectares of forest. And, oops, did I do something wrong? Yes, I did. And this is based on, because some of them, there is a great debate. Are they two story, one story houses? So we decided to do it in between. And since I told you that quite a lot of them are burned, so you need about 760 hectares of forest to burn them. And we know that because we made an experiment. We built two houses, and we burned one of them. And at this point, I would like to remind you that this is where in the forest step. We are not in Northern Europe. We are not in where there is loads of wood.  Food, sorry, wood is very, very scarce there. So think about that before, you know. That's something which nobody talks about, and I'll talk about later why. So this is the first image, the second image, oh, sorry. And here I want to turn the question of the session the other way around. According to which definition of a village, this is a village. How? Having in mind that the critical mass of that kind of settlement, about 80%, 80 to 20%, is about, I'll give it a go. I'll go and say it's one hectare. They're not one hectare, but let's say they are one hectare. So one hectare village, and 238 hectare village. How is 300, oh, 3,000 delegates of EAA, the same as the 30 delegates of EAA? Just tell me, how? How do we function together? How do we organize logistics? How we go, how is it the same thing? Because that's what we're told to believe. And also I would like to ask, how is that neolithic?  How is that happening? And how is that possible? The second image is that, is the Poland Diagram, which I appreciate you can't see, but I'm prepared to share it, if you want to come and see it in more detail. So I'll summarize it for you. Yesterday I hosted a session about the crisis in archaeological theory, and then Tim Taylor finished the slide and said, we have to stop saying, we have no evidence for, we have to start saying, we have evidence that there is no, so that's why I took that, and what I'm saying now, so we have evidence that there is no for a massive deforestation, rather than more subtle way I've tried to put it yesterday. So we have low demolition, and we have no micro charcoal, no micro charcoal, evidence for massifying, don't forget, almost two thirds of these things were burnt, and we have no evidence for massifies. And the reason I want to put these two images next to each other is because I've been giving a serial, I'm not more than me, but the other co-authors, we have been giving that talk or variants of that talk along the side many times, and we have different reactions from positive, like how that is possible, something is wrong, or let's figure it out. And on the basis of these positive things, we sort of went back to the drawing board and tried to see what may have happened, for example, whether there is a hiatus, the sedimentation of hiatus, something that may explain that. And we are trying to remodel that, and obviously there is nothing of the kind. So other reactions were, well, why don't you move the occupation somewhere along the line where it will suit you best, but not with these terms, but in that kind of sentence. And the most radical of all, I can just forget about it. Just forget about it. And this is why, why forget about it? Because there is an assumption. There is a great assumption that these sites are built at once, lasted to 50 to 80 years, burned at once, and therefore, there should be this massive occupation. Well, there is obvious contradiction between two images that I showed you. And I suggest we don't make assumptions, but we do something else. So we stop with the assumptions and we do alternatives. So there are two other talks about this site on this conference, and you haven't seen it where have you been? Because now I'm going to tell you yet a third one. So the other two are just in the pipeline for publishing, so you haven't missed it. You will see. And the alternative I have to take, Manuel, who has been very persistent and was sort of trying to push me in the direction to think about different kind of social organization, which is he's a co-editor of a volume, and that the full version of that will contain a volume that Manuel is co-editing, and he pushed me in the direction of thinking of bottom-up kind of organization, which is we all say, oh, without planning. How does that go? Right. Let's see. So the alternative I took is to look at, I know that there's a huge debate, well, huge. There is a debate on segmentary society and oncology. I'm not going to talk about those. What I'm inspired here is by Councilor Dupont, who was his anthropologist, who is a very good article about the failure of the colonial authorities when they're going to sub-Saharan Africa and expecting exactly what he's coming with his colonial path. One man in charge, and I'll go to see that other man in charge, and everything will be sorted, only to find out that there is no such thing, and there are these invisible ties across the landscape, and there is this massively resistant society, which actually functions in a different way, which the colonial power cannot cope with that. So I'm taking that as an inspiration of my model, and the second thing that I'm taking for the inspiration of my model, this is an archaeological one. This is in central Mexico, and there is a lot of evidence that exactly at the moment of the conquistador, so there is a lot of written evidence for this. And basically, what we try these oncologists to do is try to see how the society function, and can we actually infer how they function on the basis of spatial, because that's what we see, we see some spatial patterns, and we can try to link the two and try to make sense of what actually is going on. So the translation of this alphabetical, which is the story from why Aztec, if you speak Aztec, Aztec, and I can't understand you well, so it's translated as a town or a king. So they don't make, they really don't, there is no difference between the two, and the, really, okay, I have to go quickly. And then what really is good about this is that the key is that the society, the function of the alphabetical that is segmentary and cellular, which is to say that each of these alphabetical has eight segments, and as you can see here, the center of these and the alphabeticals are these squares. And if you populate that, the important point here to see is that it functions in that way, it goes, it rotates. And the rotating suggests the tribut, the rotation, the pattern in which every of each cells has to be to the, it's going to be actually that which is here. And if you put the archaeological sites around, you can get, that's the point that he's made, he made totally wrong decisions, totally wrong implications, because this is one thing, basically. But if you see it like that, what you can eat or as it goes, that's what we do, is that there is an open core in which these things are native to that one, actually that belongs to that one. So there is no specific identity which is formed here. The other thing that will come out of that, because there is this different density, you will say, oh, there is a high density, this is countryside and this is central, there is no such thing, it just, it was fine just now. And then you will say that there is three, three way carrot, well there is no three way carrot because this is the same thing. Okay, so, right, so this is what is the current theory, I have no time to tell you about that, so that's why I'm going to tell you so. So what are the reasons that people can actually get together? These are the positive differences what people get together, not the negative reasons which I'll put forward, I see the difference that there are people coming in, I suggest that this is why people get together and what they get together, that's what they do. They do these things, about 400 houses and that's how they start to be in that phase. And according to distributed governance and what is that, okay? So I suggest that only 400 houses will occupy problems in the whole thing and this is about what is the amount of population. I suggest that seven to 10 houses will burn every year and then also that every year, one of them, similar to what I was saying about the rotation model was actually irresponsible for the running of the place and what was the place doing? What were they exactly? What people call urban function. So that's what it is and one of these plans was responsible for doing that. And how are they eating and what they were eating?  But crucially, and that's where it comes from the second phase of society and what Kurt was saying.  Do we have them? I can tell you, but yes, we do. If you go on one of the other talks, you would hear that the social catchment area, not to the rest of the social catchment area of our site is about 100 kilometers. Do we have sites in these 100 kilometers that will actually be able to fit and help this cause? Yes, we do. There are caveats to that, but I have no time to tell you. What are the caveats? Is it the one, this is the last one. No, this is the, right. Okay, so if you ask us to put what we think is urban and we make a list of it, I can bet you by the end of the day, we'll never agree that what I'm presenting about the last person is presenting is the same thing. You'll say no, and why is that? Because we use this criteria. But we have to, where it's very popular, everybody's using it, but they keep forgetting that he said also that you have to make that this is highly contextual thing. This is not an absolute thing, it's contextual thing and that's why we have to think about it. And I'll give you an example. I was born in this place, which is one million people and it's a city. It's the capital of Bulgaria. I live in that place, 15,000 people have it. And it's also a city because it has a cathedral. These two have two different criteria of why there is a city. And nobody seems to have a problem with that. But when we go to the prehistory, we have a great problem to use different criteria. Why? So what I suggest, we have to do a relational approach. We have to look at the evidence in a different way, not absolutely, because you will go nowhere. These two places will never be seen if you look to your absolute categories. And therefore, in a belief girl, should we make sense only when you look at it in a local context, which really stands out. It was very, very, very different rather than in absolute things. It will never compare to the nearest and I don't really invite you to compare it to the nearest because it's not the same thing. So that's the conclusion. So I suggest that we should not do assumptions and we should not dismiss evidence just because they don't fit what we want to hear. Sorry. Then I suggest that the model that comes with this, I didn't have time to talk about materialized hierarchy. But this is, now we are okay with it. These two images at the show at the beginning are okay. And urban is not a fixed category. And we have to think, it's a highly contextual thing. Thank you very much. I think I did it on time. Thank you very much. Thank you very much. Thank you.


The Bemidji Fire Department has been selected for a national program to help reduce the future of wildfire risk and cost. Josh Peterson has more. Over the past five years, Bemidji and the surrounding areas have seen an increase in the amount of wildfire activity. That is one of the reasons why Bemidji has been selected as one of five new communities from across the country to receive technical assistance from community planning assistance for wildfires. A national program that helps reduce future wildfire risk and cost. We ran into an opportunity here to apply for a grant to provide us some assistance in assessing our community and ultimately developing some plans to minimize the impact of wildfires on the Bemidji area. Thanks to a collaborative effort by the Bemidji Fire Department and the Greater Bemidji Area Joint Planning Board, they were able to secure this opportunity. Our involvement will be community planning, helping plan for prevention of wildfires. Being selected for this honor is a very big deal and not just in the monetary value but in the amount of training and education that will be brought back to the Bemidji area. With this SIPA award, we're going to be able to really take that to the next level and get some technical assistance from national experts to help not only the Fire Department but the Greater Bemidji Joint Planning Board. These trainings and programs come at a crucial time for the Bemidji area. Implementation is expected to begin soon. Our first step is going to be a community-wide risk assessment to identify our areas and then we'll start working with some of the national experts on developing some of our plans. This program will now put Bemidji on a national scale with tools and resources to provide a greater and safer community. In Bemidji, I'm Josh Peterson, Lakeland News. She's Fire Chief and others will attend this SIPA training and conference beginning November 1st. If you've enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland Public Television.


Yo, what's going on man? It is Friday. Happy Friday to everybody. I hope you all have an amazing weekend By the way, and today we are here on wait wait. Let me scroll up. Oh my god. We're here on a train fan But I'm a train fan J. T's channel. He actually commented on my video He's like hey, oh bro mind checking out my videos You can react to them and whatnot because they are sort of related as we can see here So shout out to train fan J. T. Thanks for letting me react to your videos of course and shout out to him Go check out his channel out make sure you go like his videos and all that stuff so far first video working be watching After the brand-name baby last This should be interesting Looks like it was made in raw black Wait, was that Donald? I believe it was not Donald Trump though. He's thanks Dude man's looks like he's worried Do the way his eyes move. This is definitely made in Roblox Man's hitting that reverse Right the next day seem like he just got there and loaded his Load whatever he had there Wait, that's a vocal right guys Oh I thought everybody was supposed to be like mutated though since it was after the blast and like their whole radiation stuff. Oh Ben all right. We got Bill and Ben here, dude. They're mutated Stormtroopers, I guess he had to get a little creative, you know. Oh my god. Did you saw their faces?  That is so messed up. Buck will have to witness this man. That is so sad Rip to them. Yeah, what's going on? What's happening to Donald? Sound like his engine is about to be blown out or something He just blew up What caused him to blow up?  He just witnessed all of this Wait, I saw Salty's name in the back there like on a sign We're salty. Yeah. All right. Well, that is it. All right for our next video.  Oh, it seems like it's getting worse by the minute. Where is he heading off to? That's what I want to know What's wrong with these trains and crashing and blowing up all the time, dude All right, so it seems like James was zooming out there and then he just like he crashed into that pile of dirt Whatever that was I could have talked exactly what it was and he couldn't stop in time I don't know man. Um Well, that is it you guys if you guys want me to react to any specific Soter following episodes. Let me know in the comments down below check them out. Definitely. Oh, that one looks cool experiment 411 We'll check that out for another time. Alright you guys Well, thank you all for watching. Thank you all for the base support as always and enjoy your Friday and your weekend And I will see you all in the next one. Peace


From Hollywood it's time now for Johnny dollar Hello Is this dr. Big B Look dr. Big B. I want you to come out here just as soon as possible It's the old cronin summer place about five miles up the river from where I know Mrs. Cronin opened it up for a party this weekend, but she was taken ill on the train coming up And I want something out there. Yeah, she's the one I want you to look at She had a prescription from her doctor in New York, but she's taken the last of it. It's apparently your heart I'm sorry. It's a dollar. I'm very busy tonight.  I think no wait a second if you're a friend of Dolly's Mrs. Cronin's do one thing take her back to New York now Tonight get her out of here fast before it's too late Tonight and every weekday night Bob Bailey in the transcribed adventures of the man with the action-packed expensive out America's fabulous freelance insurance Investigator yours truly Johnny dollar From special investigator Johnny dollar at Wells Falls, New York to the home office surety mutual and trust company Hartford, Connecticut Assignment the cronin matter a half million dollar necklace expense account continued Item seven five dollars and forty cents taxi I figured I'd find dr. Bigby in one of the local pubs But I covered them all in about 30 minutes no sale and unfortunately Bigby was the only doctor in Wells Falls Worse the local drug is couldn't fill Mrs. Cronin's prescription the nearest chance was Tupper Lake 25 miles away Back out at the Cronin place I turned the taxi over to Jason Prell Mrs. Cronin's business advisor and he took off for Tupper Lake to look for the medicine Then I went looking for Mrs. Atherton a village woman who had been housekeeping on the estate since the place was built I found her in the kitchen Storms brewing up coming out of the mountains. It'll hit us for a morning. They always come in the night I guess you've seen a lot of storms in these hills Mrs. Atherton. They've here all my life never been out of them It's miss Atherton not Mrs. Oh She's the Mrs. Up in the bed Even if she is a widow Little dolly. Mrs. Cronin till death to us part Did you know Barnaby Cronin miss Atherton? Yes, I knew him of course. I knew him. I worked here. Oh, yes You were here then What kind of a man was he? Like any other man out according to dolly. Mrs. Cronin she apparently worshiped him still does in fact dolly's always Worshiping something everybody was always worshiping her She had us all dancing to her tune and without even trying you know her back then she was born and raised here in the village I thought everybody knew that No, that's when I missed We used to work together waiting tables at the summer hotels around here. That's where Jason Prell saw her Told her she ought to be on Broadway She left the town the next week didn't come back again till after she and Barnaby was married And she got him to spend a fortune to build this place for her. Well, I guess he had the fortune to spend. Oh, yes She married well count on dolly for that Always got whatever she wanted never even had to ask Things were just given to her always. Yeah, probably so But she's been pretty generous herself Like keeping you on here for instance when the house has been closed up for years with nobody using it She's the dancing darling all right right to the end Well, I feel excuse there was something else. I wanted to ask you miss Atherton I'm not one to talk ordinarily, but you got me started. This is not about mrs. Cronin at least not directly She was taken ill on the train. I don't think it's serious But I wanted a doctor to look her over the only one in the village seems to be a man by the name of big B big B He's the coroner here, but he's not a doctor. No Not anymore still calls himself one, but he lost his license ten years ago He's a drunken shot. Yeah, I kind of figured But he sobered up fast when I told him on the phone that the patient was mrs. Cronin He refused to come out told me to get her away from here fast and then he hung up on me forget him He couldn't do any good, but I'd like to know why he acted that way Do you happen to know any reason? Big B is a drunk. Who knows what his reasons are I? Thought you might better ask him What difference does it make anyway? You can't help her nobody can't what do you mean?  That wasn't any surprise to her.   Yes in this very house a heart attack it was called He came up on the afternoon train That's strange It was the same kind of night A storm like tonight Strange how things move and patterns Were you here with him miss Atherton? Barnaby died alone and the doctor Big B Miss Atherton was the doctor I'm sorry. I was thinking The bridges were washed out Big B didn't get here till the next morning Wouldn't have mattered. He couldn't have done anything Nobody could have When it's time for a thing to be done, it's done Nobody can stop it nobody It was a strange year ominous and oppressive with a feel of violence in the air Even the house itself added to the feeling Furnished lavishly in a style 30 years forgotten. It seemed garish now old and tired and lonesome Like mrs. Cronin herself who'd planned a grand party for all her old friends and instead lay ill and alone in the bedroom upstairs The queen gave a party and nobody came all dressed up no place to go Yeah, it blew me Jason Prell came back from Tupper Lake with a medicine Miss Atherton served a dinner of sorts served it in silence and we were left to our own devices Five guests and a mansion built for a hundred Prell stayed pretty much to himself Lovely Laura Dean with that air of knowing innocence and vehicle to shorty Weber into teaching her some of his old dance routines And they cranked up an old phonograph in the music room And me I just stood at an open window and watched the rain come down and tried to think That's the perfect touch. It's exactly what the evening needed that music Sylvia really cornball, isn't it? No, no Johnny I meant the thunderstorm an isolated old mansion Fabulous necklace of diamonds and emeralds weird housekeeper a hostess lying ill And now rain shades of a house of usher. That'll make a good lead for your magazine store I should have stayed in New York and just written it not lived it. Oh, I thought you were the big take a chance girl Miss Blake danger mystery adventure Don't those things appeal to you? Maybe is there any of that lying around somewhere? There may be before the night's over all I can see at the moment is sheer boredom You have to know it a look the bottom of that scotch glass for instance. Oh, it's just killing time. Oh I've been wanting to ask you Johnny How'd you get that cut on your head? It's a long story. It happened on the train. I know that you didn't have it when we left a sudden stop I fell over my suitcase. Sure. You did backwards. Huh? It's on the back of your head Somebody made a try for it. Didn't they on the train coming up? Well, I don't know what they were trying for Wasn't time to ask maybe they even got it That's the way you were betting wasn't it that it wouldn't be just an attempt That somebody was going to get it and get away with it. Did they is that what happened? Is it gone? All right, just stand there and grin then Rain I'm going back to the city tomorrow. You are well. Don't smother me with your pleading Stick around Sylvia things may get better including the music You know in a way, I hope somebody did get the circle of fire why what good is that fabulous necklace doing her now lying up there? She's had everything she ever wanted life's been too easy on her.  That's the usual advice You said it I didn't well you're a man Johnny. Why don't you smooch with me be a way of passing the evening killing time What are you Johnny wait? Johnny Why did you do it because you wanted me to and because I wanted to? Adventure mystery danger Who's bored? Who's going back to the city? Those doctors are right Dollar could I talk to you for a minute? Why not shorty? What's on your mind? I don't know exactly why you call us all together in here was mrs. Cronin's idea She set it up with me earlier. Well, I ain't got nothing to do with what I wanted to say You see you see me in a bad light there yesterday your dolly's apartment Well, you found a gun and me you know about my record made it look better I know it did but so help me mr. Dollar everything. I told you was the gospel truth Yeah, I'd break my arm before I do anything to harm dolly in the least bit You see I've been in love with that woman for 35 years Like the broken heart when she married Barnaby But I always know I didn't have no chance right from the start. She was up there big somebody Me I was a nobody but I'd still die for her any time. That's all mr. Dollar I just wanted you to know They were all there Gathered around the big dining table watching me and waiting Mrs. Cronin had asked me to arrange it. She said that was the main reason they'd come and she didn't want to disappoint them I told them that And then I took the circle of fire from my pocket and laid it on the table They all reacted in different ways Laura Dean gave a gasp in her eyes open wide and Sylvia Sylvia Blake was fascinated hypnotized. Yeah, you should have seen it on her back in the old days It's sparkled even twice as much So that's what this is all about. It's only jewelry. I've seen it before but there was one special reaction I was looking for and I got it Jason Prell's face went white Mr. Prell you seem surprised I Wasn't carrying the necklace in its case the case you stole from me on the train I was carrying it loose in my pocket. What did you do throw the case off the train without even bothering? I went after him but he'd already disappeared somewhere down the hall He knew the layout of the house, and I didn't I searched the different rooms quickly as I passed but there was no sign of He couldn't have reached the floors above but he might have gone down toward the game room and lower halls I ease my gun from its holster and started slowly down the stairs and At that moment every light in the house went out There'll be another intriguing episode in our story of the Cronin matter tomorrow tomorrow a white lie bullet from the darkness and Death comes in out of the rain Join us. Want you yours truly Johnny dollar Yours truly Johnny dollar starring Bob Bailey is transcribed in Hollywood written by Les Crutchfield It is produced and directed by Jack Johnstone Be sure to join us tomorrow night same time and station for the next exciting episode of yours truly Johnny dollar Roy Rowan speaking


So the next speaker is Prabhakar and she's going to tell us about popular matchings again. Thanks. So this paper is on the popular roommates problem, which is a popular matchings problem in general graphs. For those who attended the workshop, I talked about popular matchings in bipartite graphs. So this is a much harder problem. Let me start from the definitions. So our input is a graph. It need not be complete though in this example, I drew a complete graph where every vertex has a strict ranking over its neighbors. So A regards B as its stock neighbor, C as its second choice neighbor and D as its worst neighbor. So let's just think of this as like participants for FST, TCS. We need to pair up people for guest house rooms and everybody has a preference on, it's not that every pair is willing to share a room also. So A would very much like to share a room with B. Well, but B has C as its top choice. C has A as the top choice. Nobody seems to want to share a room with D, but D has its own choices. And so that's our input. And this is actually called a roommate's instance, exactly from the application that I talked about. We want to pair up people so that they become roommates. And this is actually an old and well studied problem. And what one seeks here is, is there a stable matching out here? So pairing up vertices corresponds to a matching. And we would like to find a stable matching. So what is a stable matching? One that has no blocking edge. So an edge blocks a matching if the endpoints of the edge would rather be matched to each other than to their respective partners. For instance, if you look at the red matching, the pair BC would rather be matched to each other than to the respective partners. That is, B is currently matched to A, but it prefers C to A. Similarly, C is matched to D, but it prefers B to D. So B and C would rather be matched to each other than to what the red matching has assigned them to. So the red matching is not a stable matching. So this is a classical theorem from. Is there an issue why you consider complete matching? In this example, because it was a complete graph on an even number of vertices, it turned out to be a perfect matching. It did not be perfect indeed. Yeah, so Galen Shapley many years ago considered, in fact they initiated the study of stable matchings in bipartite graphs where it's easy to show that stable matchings always exist and they can be efficiently computed. Well unfortunately, in general graphs or non-bipartite graphs, stable matchings need not always exist. This very same instance shows that. So as I already discussed with Sanjay, any stable matching here has to be perfect because it's a complete graph on an even number of vertices and we could just run through the three possibilities, the three perfect matchings here and each of them has a blocking edge. So there is no stable matching in this graph. So does a roommate's instance admit a stable matching or not? So this was an old question and this was answered by Rob Irving in 1985 who showed a linear time algorithm to solve this problem. So given an instance, you can decide in linear time if there is a stable matching or not and if so to find one. However, as we saw with our starting example, there are simple instances with no stable matchings. So that motivates the question, maybe forbidding blocking edges is too restrictive a notion of stability. Why don't we ask for a more relaxed notion of stability and that's where popularity comes in. So I hope I can convince you that popularity is a natural relaxation. So it's something that the view of the retina is polynomial time identifiable whether recognizable whether there's a stable matching or not. If there is no stable matching, is there a polynomial time algorithm to find out the largest number of edges in a matching which is stable? That is to find one with minimum number of blocking edges or some such notions, so they're all NP-hard. Yeah, so indeed. Yeah, so popularity, I hope you'll be convinced at some point is a natural relaxation of stability. So this works by comparing any pair of matchings by holding a head-to-head election between them. So how do we compare a pair of matchings? Ask every vertex to vote for one matching versus another. So maybe I just show it by this example. We have two candidates here, the blue matching and the red matching. And let's say we ask every vertex, are you happier with the blue matching or the red matching? Every vertex just looks at its partner in the blue matching and its partner in the red matching. It's not concerned with what partners others have obtained. So in this election between red and blue matchings, vertex A is happier with the red matching. It gets its top partner and in blue matching it gets its worst partner. However, the remaining vertices B, C, D prefer the blue matching. Each of them gets a better partner in the blue matching. And so in this head-to-head election, the blue matching wins three votes and the red matching wins one vote. And we compare two matchings by just looking at the difference between the votes that one matching obtains and the other matching obtains in their head-to-head election. And a matching is popular if it never loses to any matching. So it loses to a matching if this difference is strictly negative. That is the other matching obtained more votes than itself. And a matching is popular if it does not lose any election. So it just count over all vertices. So the blue matching, as I said, in the red versus blue election, the blue matching got the votes of B, C and D, three votes. And the red matching got one vote. So it's three versus one. And delta red, blue would be minus two. So red for sure is not popular. Whether blue is popular or not, it's too early to say that you have to compare it against every matching and ensure that it doesn't lose against any matching. So the notion of popularity was introduced more than 40 years ago by Garden Force who observed that it's indeed a relaxation of stability. Every stable matching is popular and it's virtually a one-line proof. So when we have an election between a stable matching and a rival matching, if a vertex V votes for the rival matching, its partner in the rival matching, M of V has to vote for S. Otherwise, the edge between V and M of V would block S and S being a stable matching has no blocking edge. So a stable matching never loses a head-to-head election against any matching. So for sure, a stable matching is popular. So delta V is zero? So we can't compare that to it. So it certainly has not lost the election. So it's still an eligible candidate for popularity. So going back to the starting example which had no stable matching, in fact, it has two popular matchings. The blue matching that we saw in the earlier election is actually popular and there's one more popular matching and indeed in the election between the blue and green matchings it would be a tie between them because neither can lose against the other. So this instance has two popular matchings. Well, there are simple instances that have no popular matchings also. If you just look at a triangle where A prefers B to C, C prefers A to B and B prefers C to A. So the popular roommates' problem is the following. Given such a graph, does this instance admit a popular matching or not? And if so, we would like to find one. Well, for all the relaxation and so on, we've paid a price. This problem is NP-hard. The stable roommates' problem had a linear time algorithm and earlier this year two different groups came up with two different proofs of this hardness, Fianza et al. and Gupta et al. So for all our motivations, this problem is hard to solve. So let's take inspiration from the vast literature on fast exponential time algorithms for hard problems. So we saw several such results in Sanjay's talk earlier. So the only algorithm we know to solve this problem is actually the brute force algorithm that enumerates all matchings in the given graph. And this could take n factorial time. Is there a faster algorithm for the popular roommates' problem? If we are ready to invest time and decide if there is a popular matching or not, because the problem, let's say, is very important to us, how fast can we do it? So our main result is that we can do this in simply exponential time. So O star is hiding some poly n factors. Let's not worry about it. The popular roommates' problem can be solved in O star k to the n time where k is a constant. But the constant is unfortunately not too good. The constant k can be bounded by 3 times c, where c is a constant involved in a recent breakthrough result by Carlin et al, who showed that the maximum number of stable matchings possible in any bipartite graph that has n vertices on each side is at most c to the n. This was a long-standing open problem. Can we bound the number of stable matchings in such a bipartite graph with an upper bound of the form c raised to n? And the bounds for c are rather... So one knows instances where it's actually number of stable matchings is lower bounded by 2.28 raised to n. So this is a loose upper bound. So Carlin et al in their papers say they believe it is much slower, but they don't really... They have not really invested time to investigate it, and the hope in future one shows better bounds. So indeed, as the bound for c improves, our bound also will improve, but as it stands now, it's like this. So can you go back? Sure. So suppose, I mean, like, is the algorithm sort of oblivious to what this bound is, in the sense that, I mean, is it the case that the algorithm runs like if you promise to me that c is the number of stable matchings? Indeed. Indeed. You're right. Exactly. So Ram Prasad was asking, does my running time kind of bounded actually by function of the number of stable matchings rather than just give a hard bound on it? Indeed. It is a function of how many stable matchings. Not the given graph, but some subgraphs and some related graphs have. So, yeah, I should be a little more careful before I say, yes, sir. So let's start from, given a matching, how easy is it to test if m is popular or not? And this actually, there are combinatorial algorithms for it, but I would rather use the machinery of max weight perfect matchings. This can be modeled as a max weight perfect matching problem under an appropriate edge weight function, which is as follows. So for any edge a, b, look at the votes a and b give to each other versus the respective partners in m. So m of a or m of b could be null also, which is the worst choice for any vertex to be left unmatched. So don't think of it as an unmatched vertex, it gets a single room, so that's a preferred state. That was just a story to begin with. So every vertex wants to be matched. Yeah, so the vote of a vertex for one neighbor versus another is plus one, if it prefers the first neighbor, minus one, if it prefers the second neighbor, zero if the two neighbors are the same. So any edge weight is one of zero plus two minus two. It could be plus one, plus one, minus one, minus one, or some combination of plus one, minus one, or both zeros when a, b is in the matching. And also it would help us to regard every matching as a perfect matching. So let's augment g with self-loops and just include self-loops for all vertices left unmatched, so that henceforth all matchings would be perfect. We also have to extend our edge weight function to self-loops and that's just the vote of a vertex for itself versus its partner in m and that would be one of zero minus one. Yeah, so the way we define this edge weight function is been defined so that for any perfect matching the weight of the perfect matching under this edge weight function is exactly the difference between the votes that n gets and m gets in their head-to-head election. And this is a characterization of popular matchings. m is popular if and only if for any perfect matching n its edge weight is at most zero. And actually though the definitions of stability and popularity seem quite different the difference between a stable matching and a popular matching is exactly due to this word perfect. m is stable if and only if the weight of any matching is non-positive and m is popular if and only if the weight of every perfect matching is non-positive. So it's easy to see both these characterizations. So popular matchings and stable matchings are actually much closer than what their definition appeared to be in the beginning. So just to illustrate the edge weight function on this graph if you look at the blue matching then in fact for both the edges in the blue matching their weights are zero and ac is a blocking edge and so its weight would be plus one one plus one which would be two for other edge weights you could just sum up the votes of the end points of the edge for each other and one could just check all these edge weights and for each self-loop the edge weight is minus one because every vertex prefers to be matched to a genuine neighbor than to itself which means it was left unmatched and it's easy to check that for any perfect matching in this graph its weight is at most zero so that's a proof of the popularity of the blue matching that for all perfect matchings their edge weight is at most zero. So let's write the LP for max weight perfect matching so this is our objective function find a matching that maximizes the sum of edge weights x sub e's are variables it's a perfect matching delta prime u is just the set of edges incident to u union the self-loop so and we also have offset constraints e square brackets b is a set of edges with both end points in the set b self-loops are not a part of e square brackets b so this is a well-known LP for max weight perfect matchings and m is popular is equivalent to saying the optimal value of this LP is zero so we argued earlier it's at most zero and in fact it's exactly zero because m itself has weight zero under this edge weight function so its dual will be interesting to us will be useful to us actually and the dual variables are alpha sub u's corresponding to these constraints and z sub b's corresponding to these constraints so every edge should be covered that's what really this constraint says self-loop should also be covered and alphas don't have to be non-negative because we talked of perfect matchings whereas z sub b's are non-negative and the earlier point that the optimal value of the primal LP has to be zero that was a characterization of popularity in the language of dual it translates to there has to be a dual feasible solution such that the dual objective function evaluates to zero and we call that has to be a dual optimal solution we call that a witness of a popular matching so in fact we can sharpen a witness so if m is popular then m always has an integral witness where alpha sub u for every vertex u has to be one of minus one plus one zero and in fact z sub b for all odd sets b is one of zero one two so this actually follows from total dual integrality of the formulation and the fact that m itself is a primal optimal solution so in fact the z sub b seem to be a little bothersome we have exponentially many variables suppose m is a matching that has a witness with far more structure let alphas be the way they were earlier but suppose z sub b is zero for all odd sets b can we say something more about m than just the fact that it's a popular matching so for that let's actually digress into fractional matchings so a fractional matching is just a vector so that for every vertex the sum of p is of edges incident to it including on its self-loop is equal to one maybe yeah so this example where p e is half for each of these three edges that's a fractional matching we are in non-bipartite graphs so a fractional matching need not be a convex combination of matchings as in this example so the function delta that we use to compare to integral matchings it generalizes easily to compare an integral matching with a fractional matching as follows just a linear definition and let's call a matching popular fractional if it never loses an election against a fractional matching and those matchings that have a witness alpha zero vector actually are popular fractional matchings and this is a stricter definition than popular matchings for instance if you look at this graph that consists of two triangles and an edge between them the red matching is a popular matching that can be checked however if you look at this fractional matching that takes each of these three edges with weight half and each of those three edges in the triangle with weight half that defeats our popular matching so in this p versus m election m gets one and half votes and p gets two and half votes because now vertices can give half votes and so this is a popular matching that's not popular fractional so popular fractional is a strict subset of popular matchings so let's go back to popular matchings I just wanted to introduce popular fractional matchings because we need it in a decomposition result that we show here any popular matching can be partitioned as m zero union m one where m zero is stable in a sub graph of our graph and on the remaining part m one is popular fractional we saw that in the previous slide what's a popular fractional matching so every popular matching actually has such a decomposition into a stable part and a popular fractional part so what really is the definition of that set C I was just writing the points I hope it's not too dense so since it's popular since m is popular we know it has an integral witness moreover we can find a witness where the sets B which have support on them under the vector Z actually form a laminar family Edmunds primal dual algorithm shows this so we can find an integral witness with a laminar structure on the sets B that have support on them and in fact all the sets B that have positive Z value due to complementary slackness they're constrained in the primal LP has to be tight so if you look at the maximal sets that have positive support on them each of them has just each of them is an odd set going by the previous constraint there's just one lone vertex that's left unmatched in each of these maximal sets and C is basically from each maximal set leave that lone vertex out take the remaining vertices and take the union over all these maximal sets that's our C and in fact m restricted to C is fractional and m restricted to the remaining vertices is popular fractional this claim is a little tricky this is straight forward so I thought maybe I would just go through it in fact the same alpha that was the first coordinate of a witness for m followed by the all zeros vector would be a witness for m restricted to the subset of vertices so we have to show that the self-loop are covered that's straight forward we have to show all edges are covered and thanks to the popularity of m and the fact that alpha that is a witness for m's popularity we have this red constraint however from the definition of C we know that there's no odd set that contains two vertices in v-c hence all edges are covered by the same alpha and it's also easy to show again by complementary slackness the sum of alpha values of all vertices in v-c the sum is zero so indeed alpha, the zero vector is a witness for m restricted to v-c so we can also sharpen our decomposition theorem to say that m0 is stable on actually a slightly larger subset and m1 is a special popular fractional matching on the remaining subset so special popular matching has an even more restrictive witness where we don't even allow alpha sub u to be zero for any vertex each alpha u is either plus one or minus one n prime is the number of vertices of v-u so our algorithm now is thanks to the decomposition theorem we can write it quite easily it's just enumerates, it just goes through all stable matchings in every sub graph and test if the union of these two matchings is popular if so we have a popular matching and when it goes through all possible combinations of stable and special popular fractional matchings and can't find their union being popular for all possibilities it just gives up and says g has no popular matching and because of our decomposition theorem we know that if there is a popular matching it has such a decomposition and we have basically done a brute force search over all this stable comma special popular fractional matchings and if we fail there is indeed no popular matching the blue part special popular fractional matchings is it easy to exactly so I am coming to that right now so Ruta asked me how easy is it to enumerate over the special popular fractional matchings indeed so I would just say that in one minute so if you look at any subset u and look at the sub graph induced on u so the result by Karleen et al tells us that the maximum number of stable matchings possible in this sub graph is c to the i where i is the number of vertices and in fact they can all be enumerated also in o star c to the i time this is an old result that is there in the monograph by Gusfield and Irving and coming to special popular fractional matchings we can show any special popular fractional matching has to be a stable matching in one of two to the t different graphs that we construct and each of them is on t vertices so each of them has at most c to the t stable matchings and we have two raised to t many of them so we can bond it by 2c raised to t so the whole machinery of stable matchings essentially gives us this bound t is the size of t- yeah exactly so the total number of candidate matchings tested by algorithm is we enumerate we go through all subsets enumerate all stable matchings on that subset special popular fractional matchings on the remaining part on the complement and that sums to 3c raised to n which was our bound for k and yeah so i do have one more result in this paper so one may say ok so instead of popular matchings if we restrict our attention to those integral matchings that are also popular fractional restrict subset of popular matchings are they easy is that a tractable class so our NP hardness proof earlier this year shows that even that subclass is NP hard however our machinery enables us to show maybe a truly fast exponential time algorithm for this subclass rather than k raised to n here i am able to show a bound of o star 2 to the n time for testing if g admits an integral matching that's also popular fractional so in bipartite graphs is there such a decomposition so bipartite graphs every popular matching is also popular fractional because fractional matching is just a convex combination of matchings and so if a convex combination defeats you it has to be the case that some integral matching itself defeats you so such a thing is obviously there will be a popular matching itself is there but we have actually nicer decompositions in bipartite graphs so but then i will have to use another new word for it but as such the decomposition is trivial in bipartite graph i am not too sure so what does this algorithm but all the we keep reducing things to stable matchings and with ties in preference list incomplete so i didn't assume complete preference list at all it was the starting graph just happened to be complete indeed indeed so ties i am not too sure because what is the notion of stability with ties there are several notions of stability something called strong stability weak stability and so one would have to be a little more careful about what we are talking about because and so strongly stable matchings need not even exist of course even stable matchings need not exist but i have to be a little careful i am not too sure how to do it with ties fractional matching which is popular that should be good yes that is easy it is a polynomial time algorithm exactly so Rohit's question was if i didn't care for integrality if i just wanted to find that popular fractional matching popular half integral matchings always exist just make a bipartite graph out of this and find a stable matching that would become a popular fractional but finding an integral matching that is popular fractional it need not exist and it is hard to find thank you


Αμία names' NOTHIS ψήλος, and professor of philosophy of science and metaphysics in the university of Athens Greece, and a member of the Rotman Field University of University of Western Ontario, Canada. I'm here to talk about scientific realism, that's a philosophical view about science, the thrust of which is at sciences in the truth business. There are various ways to understand and define scientific realism, but my own preferred way is to understand scientific realism as consisting of three philosophical phases, One Metaphysical, one semantic and one epistemic. The Metaphysical thesis says that the world has a definite and mind-independent structure. The semantic thesis is about scientific theories. It says that scientific theories are truth-condition descriptions of the intended domain, hence they are capable of being true or false. The theoretical terms which feature in scientific theories have putative factual reference. So if scientific theories are true, then the unobservable entities, they populate the world. Finally, there is epistemic thesis and the claim that mature and predictably successful scientific theories are well confirmed and approximately true. Hence entities which are posited by scientific theories or at any rate entities very much like those posited in habit the world. You might wonder why three theses about scientific realism. Now the first, the Metaphysical thesis, is meant to make scientific realism distinct from anti-realist accounts of science, be they traditional idealist and phenomenalist accounts or more modern verificationist accounts, a la dame or the middle pattern. What is at stake in this debate? At stake, in my view, is the possibility of divergence between what there is in the world and what is issued as existing by a suitable set of epistemic practices and conditions. The realist commitment to the main independence of the world implies that if the unobservable entities exist, they exist independently of our ability to be in a position to know, verify, recognize, etc. that they do. The second thesis, which might be called semantic realism, makes scientific realism distinct from eliminative instrumentalist and reductive empiricist accounts. Eliminative instrumentalism, a view that was developed in the early 20th century by various philosophers, takes the cash value of scientific theories to be fully captured by what theories say about the observable world. This position typically treats theoretical claims as syntactic mathematical constructs which lack truth conditions, hence they lack any assertory content. They don't say anything about the world really. Reductive empiricism on the other hand treats theoretical discourse as being disguised, talk about observable entities and their actual and impossible behavior. It is consistent with the claim that theoretical assertions have truth values, but understand the truth values reductively. They are fully captured in an observational vocabulary. Opposing these two positions, scientific realism in its semantic stripe, is an ontologically inflationary view, understood realistically the theory admits of a literal interpretation, that is an interpretation in which the world is populated by a host of unobservable entities and processes. So electrons, molecules, DNA molecules or whatever are part and parcel of the furniture of the world according to the scientific realist position. The final element of scientific realism is the epistemic thesis which I call epistemic optimism. It is meant to distinguish scientific realism from agnostic or skeptical versions of empiricism. The thrust of this thesis is that science can and does deliver theoretical truth, no less than it can and does deliver observational truth. So theory does not tell us only about what we see in the world, but it tells us about what we don't see in the world in its unobservable structure and content. It's an implicit part of the realist thesis that the amplitude of abductive methods employed by scientific scientists to arrive at their theoretical beliefs are reliable.