2011/07/05 (火)
English Acquisition IAk, IIAf, 2011 第11回 (全13回)
黒田 航 (非常勤)
Tuesday, July 5, 2011
English Acquisition IA k , IIA f , 2011 11 ( 13 ) ( ) - - PowerPoint PPT Presentation
English Acquisition IA k , IIA f , 2011 11 ( 13 ) ( ) 2011/07/05 ( ) Tuesday, July 5, 2011 Web URL http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures.html
2011/07/05 (火)
Tuesday, July 5, 2011
✤ URL
✤ http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures.html
✤ 予習や復習に使って下さい ✤ 解答もこのページから入手可能
Tuesday, July 5, 2011
✤ 最期の授業は任意参加のボーナス試験です
✤ 出席回数の足りない人は任意でないです
✤ 授業でやったのと同じ課題を行なう
✤ ハズレがアタリに ✤ アタリはアタリのまま
Tuesday, July 5, 2011
✤ 今のままではFの方々
✤ EA1Ak ✤ 中島 裕貴 ✤ EA2Af ✤ 藤本 拡二
✤ 気をつけた方がよい方々
✤ EA1Ak ✤ 中尾 健太郎, 松田 朋也 ✤ EA2Af ✤ 原 将樹, 西河 拓哉, 武藤 弘平
Tuesday, July 5, 2011
✤ 前半30分
✤ 休憩5分 ✤ 後半40分
Tuesday, July 5, 2011
Tuesday, July 5, 2011
✤ 参加者: 46人
✤ 平均点: 59.48; 標準偏差: 9.12 ✤ 最高点: 78.85; 最低点: 44.23 ✤ n = 52
✤ 得点グループ
✤ 40点後半が中心のグループ? ✤ 55点後半が中心のグループ ✤ 65点後半が中心のグループ?
Tuesday, July 5, 2011
✤ 受講者数: 29
✤ 平均点: 30.93/n [59.48] 点
✤ 標準偏差: 4.74/n [9.12] 点
✤ 最高点: 41.00/n [78.85] 点 ✤ 最低点: 13.00/n [44.23] 点
✤ n = 52
✤ 得点グループ
✤ 二極化している
Tuesday, July 5, 2011
✤ 受講者数: 17
✤ 平均点: 28.26/n [54.36] 点
✤ 標準偏差: 5.92/n [11.38] 点
✤ 最高点: 45.00/n [86.54] 点 ✤ 最低点: 19.50/n [37.50] 点
✤ n = 52
✤ 得点グループ
✤ 実力がハッキリ分れている
Tuesday, July 5, 2011
Tuesday, July 5, 2011
Tuesday, July 5, 2011
✤ 参加者: 46人
✤ 平均: 0.71; 標準偏差: 0.07 ✤ 最高: 0.87; 最低: 0.55
✤ 正答率のグループ
✤ 0.7後半が中心のグループ Tuesday, July 5, 2011
✤ 参加者: 29人
✤ 平均: 0.72; 標準偏差: 0.07 ✤ 最高: 0.85; 最低: 0.55
✤ 正答率のグループ
✤ 0.7が中心のグループ Tuesday, July 5, 2011
✤ 参加者: 17人
✤ 平均: 0.70; 標準偏差: 0.08 ✤ 最高: 0.87; 最低: 0.56
✤ 正答率のグループ
✤ 0.6後半が中心のグループ ✤ 0.7後半が中心のグループ Tuesday, July 5, 2011
Tuesday, July 5, 2011
Tuesday, July 5, 2011
✤ 1. talk => topic ✤ 2. ridiculously ✤ 3. this ✤ 4. things ✤ 5. second ✤ 6. dumb => done,
don’t
✤ 7. aspects =>
aspect
✤ 8. resources =>
resource
✤ 9. foolproof =>
fulproof, full-proved
✤ 10. decisions =>
dicision, dicisions
✤ 11. face ✤ 12. really ✤ 13. create ✤ 14. sense => sence ✤ 15. deal => do ✤ 16. there’s ✤ 17. people ✤ 18. worry ✤ 19. question ✤ 20. human ✤ 21. These ✤ 22. with => family ✤ 23. technologies =
technology
✤ 24. from => for ✤ 25. contexts =>
contact(s), content(s)
✤ 26. financial ✤ 27. maybe => make ✤ 28. stuff => self, so ✤ 29. suck => use ✤ 30. currency ✤ 31. look ✤ 32. enclosures ✤ 33. figures ✤ 34. food ✤ 35. at ✤ 36. looking ✤ 37. paying ✤ 38. born ✤ 39. entering =>
into, entry
✤ 40. different ✤ 41. price => place ✤ 42. shorter =>
shoulder, showed, showder
✤ 43. who ✤ 44. came => keep ✤ 45. messing =>
massing, nothing
✤ 46. enough ✤ 47. possibility ✤ 48. impatient =>
efficient
✤ 49. wrong => long,
along, alone
✤ 50. experiment ✤ 51. handed =>
hear, heard
✤ 52. Donate =>
don’t
Tuesday, July 5, 2011
✤ I wanna start my [1. talk] today with two observations about the
Tuesday, July 5, 2011
✤ But of course, there’s a [5. second] observation about the
Tuesday, July 5, 2011
✤ But both of these two embarrassing examples, I think, don’t highlight
what I think is most embarrassing about the mistakes that humans make, which is that we’d like to think that the mistakes we make are really just the result of a couple bad apples or a couple really sort of FAIL Blog- worthy [10. decisions]. But it turns out, what social scientists are actually learning is that most of us, when put in certain contexts, will actually make very specific mistakes. The errors we make are actually
immune to lots of evidence. When we get negative feedback, we still, the next time we’re [11. faced] with a certain context, tend to make the same
human nature. What I’m most curious about is, how is a species that’s as smart as we are capable of such bad and such consistent errors all the time? You know, we’re the smartest thing out there, why can’t we figure this out? In some sense, where do our mistakes [12. really] come from?
Tuesday, July 5, 2011
✤ And having thought about this a little bit, I see a couple different
Tuesday, July 5, 2011
✤ But [16. there’s] another possibility that I find a little bit more worrying,
which is, maybe it’s not our environments that are messed up. Maybe it’s actually us that’s designed badly. This is a hint that I’ve gotten from watching the ways that social scientists have learned about human errors. And what we see is that [17. people] tend to keep making errors exactly the same way,
in certain ways. This is a possibility that I [18. worry] a little bit more about, because, if it’s us that’s messed up, it’s not actually clear how we go about dealing with it. We might just have to accept the fact that we’re error prone, uh incl—, try to design things around it.
✤ So this is the [19. question] my students and I wanted to get at. How can we
tell the difference between possibility one and possibility two? What we need is a population that’s basically smart, can make lots of decisions, but doesn’t have access to any of the systems we have, any of the things that might mess us up —no [20. human] technology, human culture, maybe even not human language.
Tuesday, July 5, 2011
✤ And so this is why we turned to these guys here. These are one of the
guys I work with. This is a brown capuchin monkey. [21. These] guys are New World primates, which means they broke off from the human branch about 35 million years ago. This means that your great, great, great great, great, great ... with about five million “greats” in there— grandmother was probably the same great, great, great, great grandmother [22. with] five million “greats” in there as Holly up here. You know, so you can take comfort in the fact that this guy up here is a really really distant, but albeit evolutionary, relative. The good news about Holly though is that she doesn’t actually have the same kinds of [23. technologies] we do. You know, she’s a smart, very cut creature, a primate as well, but she lacks all the stuff we think might be messing us
context as humans? Does she make the same mistakes as us? Does she not learn [24. from] them? And so on. And so this is the kind of thing we decided to do.
Tuesday, July 5, 2011
✤ My students and I got very excited about this a few years ago. We said, all
right, let’s, you know, throw so problems at Holly, see if she messes these things up. First problem is just, well, where should we start? Because, you know, it’s great for us, but bad for humans. We make a lot of mistakes in a lot of different [25. contexts]. You know, where are we actually going to start with this? And because we started this work around the time of the financial collapse, around the time when foreclosures were hitting the news, we said, hhmm, maybe we should actually start in the [26. financial] domain. Maybe we should look at monkey’s economic decisions and try to see if they do the same kinds of dumb things that we do.
✤ Of course, that’s when we hit a sort second problem —a little bit more
methodological —which is that, [27. maybe] you guys don’t know, but monkeys don’t actually use money. I know, you haven’t met them. But this is why, you know, they’re not in the queue behind you at the grocery store
Tuesday, July 5, 2011
✤ So now we faced, you know, a little bit of a problem here. How are we
actually going to ask monkeys about money if they don’t actually use it? So we said, well, maybe we should just, actually just [29. suck] it up and teach monkeys how to use money. So that’s just what we did. What you’re looking at over here is actually the first unit that I know of of non-human [30. currency]. We weren’t very creative at the time we started these studies, so we just called it a token. But this is the unit of currency that we’ve taught our monkeys at Yale to actually use with humans, to actually buy different pieces
✤ Like most of our money, it’s just a piece of metal. As those of you who’ve
taken currencies home from your trip know, once you get home, it’s actually pretty useless. It was useless to the monkeys at first before they realized what they could do with it. When we first gave it to them in their [32. enclosures], they actually kind of picked them up, looked at them. They were these kind
actually hand these tokens over to different humans in the lab for some food.
Tuesday, July 5, 2011
✤ And so you see one of our monkeys, Mayday, up here doing
Tuesday, July 5, 2011
✤ So the monkeys get really good [35. at] this. They’re surprisingly
Tuesday, July 5, 2011
✤ The way this works is that our monkeys normally live in
Tuesday, July 5, 2011
✤ The salesmen were students from my lab. They dressed
Tuesday, July 5, 2011
✤ You can see Honey, very good market economist, goes with the guy
Tuesday, July 5, 2011
✤ Well, we already saw anecdotally a couple of signs that they
Tuesday, July 5, 2011
✤ We were a little [48. impatient] so we wanted to sort of speed
✤ So imagine that right now I [51. handed] each and every one of
Tuesday, July 5, 2011
✤ Laurie Santos: A monkey economy as irrational as ours の後半
✤ 今日の課題の長さ: 9分
✤ 穴埋め方式
✤ 長い目のユニットごとに2回反復 ✤ 課題として大変みたいなので,間を空けます
Tuesday, July 5, 2011