牛津逻辑推理入门 - 4.怎么样才是好的论证？正确的真实的.

视频全文转录（中英双语）

以下为完整中英双语转录，已加标点。英文在前，中文在后，逐段对照。

由 Groq Whisper 转录 → M3 B 方案整文标点 + 分段 → M3 段号保留翻译 → 逐段对照。

[段 1]

Okay, here we are at week four. Well done for staying with us so far. This week we’re going to be looking at how to evaluate arguments, how to tell whether an argument is a good one or a bad one, and we’ll start with inductive arguments. Right, let’s get started today. Last week we learned how to analyse arguments, and what I meant by that was how to identify them and how to set them out logic book style. I gave you six steps to analysing an argument, and these are the only steps. Another thing that’s become clear to me from emails and questions I’ve had this week is that a lot of people are trying to evaluate an argument to say whether it’s a good argument or a bad argument as they try and analyse it. Well, don’t, because you’ll always be led astray if you try to do that, especially with a complicated argument like the one we looked at last week. So follow just these steps. Don’t do anything else to the argument. Don’t say, I think the conclusion shouldn’t have a not in it here, and take the not out. Nots are really very important, and they shouldn’t be added in either if they’re not there. So just follow these steps. That’s all you need to do. I’m not suggesting it’s easy. In fact, this is the hardest thing you’ll ever do in logic.

[译文 1]

好的，我们来到了第四周。能坚持到现在，大家做得很好。本周我们要学习的是如何评估论证，如何判断一个论证是好是坏，我们先从归纳论证开始。好了，我们开始今天的课程吧。上周我们学习了如何分析论证，我所说的分析是指如何识别论证以及如何用逻辑学课本的方式把它们列出来。我给了你们分析论证的六个步骤，而这些是仅有的步骤。从这周我收到的邮件和提问中，还有一件事变得很清楚，就是很多人在试图分析论证的同时，也在试图评估论证以判断它是好论证还是坏论证。嗯，不要这样做，因为如果你那样做，你一定会被带偏，尤其是像上周我们看的那种复杂论证。所以请严格按照这些步骤来做，不要对论证做任何其他改动。不要说，我认为这里的结论不应该有"不"字，然后把"不"去掉。“不"字非常重要，如果没有也不应该加上去。所以就严格遵循这些步骤。这就是你需要做的全部。我并不是说这件事容易。事实上，这是你在逻辑学中做过的最难的事情。

[段 2]

Computers can’t do this. Only we can do this. A computer can evaluate arguments very easily by appeal to just a very sillyarguments very easily by appeal to just a very simple algorithm, but what it can’t do is translate an argument in English into a formal language. Hopeless. Computers can’t do that, or at least not unless they’re very, very, very simple. So those are the steps that you must take to analyse arguments and don’t try and evaluate them at the same time. okay we did see that although we needed to paraphrase arguments in order to complete these steps in other words we had to add in things that I mean instead of it we put she or something like that or that wasn’t a good example but instead of it it was tried to tickle him or do you remember so we had to paraphrase arguments to complete these steps but by paraphrase, I just mean put what’s there in different words, not change the meaning of anything and certainly don’t add in any meanings or take away any meanings. Paraphrase is just changing the words so that the argument structure becomes clearer. Do you see the difference? And again, you’ll probably need a bit of practice before that comes easily because it really is a temptation to evaluate the argument and to change its meaning if you think it would be clearer if so and so said this rather than that but try to avoid that because what you’re trying to do is identify the arguments as somebody else’strying to do is identify the arguments that somebody else is making, not the argument that you would make if you were in his position.

[译文 2]

计算机做不了这个。只有我们才能做这个。计算机可以非常容易地通过一种非常简单的算法来评估论证，但计算机无法做的是把一个英文论证翻译成形式语言。完全不行。计算机做不到这一点，或者说，除非论证非常简单，否则它们做不到。所以这些是你在分析论证时必须采取的步骤，不要试图同时评估它们。好的，我们确实看到，虽然我们需要改述论证来完成这些步骤——换句话说，我们必须加入一些东西——我的意思是，比如我们把"it"替换成"she"之类的，或者那不是一个好例子，但比如"it"实际上是"试图挠他痒痒"之类的，你还记得吗？——所以我们必须改述论证来完成这些步骤。但我所说的"改述”，只是指用不同的词来表达已有的内容，而不是改变任何意思，当然更不能添加或删减任何含义。改述只是换一种说法，让论证结构变得更加清晰。你看出其中的区别了吗？同样地，你可能需要一些练习才能轻松做到这一点，因为不去评估论证、不改变其意思确实很难——如果你觉得如果某人这样说而不是那样说会更清楚，你就会有这种冲动。但请尽量避免这样做，因为你试图做的是识别他人正在做出的论证，而不是如果换成你处在他的位置你会做出的论证。

[段 3]

Okay, there’s the point about analysing arguments is in the hope that you might learn something. And you won’t do that if you’re imposing your own grid of understanding onto someone else’s argument. Okay, so paraphrase, but don’t change the meaning. We also saw that it’s necessary to bring to bear our understanding of the argument. For example, do you remember the suppressed premises that we added last week? I mean, we had quite a tussle with some of them, didn’t we? Some of them turned out, some of the things that we thought might be suppressed premises turned out actually to be a matter of inconsistent terms or something like that. So we have to bring to bear our understanding of the argument and what follows from that, but don’t read into the argument anything that isn’t actually there. If a suppressed premise is there, it’s usually pretty clear that that’s a suppressed premise of the argument. It’s a premise that ought to be there, but isn’t. So all you’re doing is making explicit something that’s already there implicitly. Okay, I think we’re… Okay, and I’ve just said it’s extremely important in analysing an argument not to evaluate it. First you identify it, then you evaluate it. Okay, any questions about all that before I move on to today?that before I move on to today. No, okay, let’s move on to today.

[译文 3]

好的，分析论证的意义在于你也许能从中学到一些东西。如果你是把自己理解的框架强加在别人的论证上，你是学不到任何东西的。好的，所以要改述，但不要改变意思。我们也看到，有必要运用我们对论证的理解。例如，你还记得上周我们补充的那些被省略的前提吗？我的意思是，我们和其中一些进行了相当激烈的争论，不是吗？其中一些，我们原本以为可能是被省略的前提，结果实际上只是术语不一致之类的问题。所以我们必须运用我们对论证及其推论的理解，但不要把论证中实际不存在的东西读进去。如果一个被省略的前提确实存在，通常很明显那就是一个被省略的前提。它是一个应该在那里但却没有的前提。所以你所做的只是把已经隐含在那里的东西明确表达出来。好的，我想我们……好的，我刚才说过，在分析论证时不评估它是非常重要的。首先识别它，然后再评估它。好的，在我继续今天的正式内容之前，关于以上这些大家有什么问题吗？没有的话，好的，那我们继续今天的内容吧。

[段 4]

What we’re going to do today is to start learning how to evaluate arguments. Now, today I’ve got down to starting with validity and truth, looking at the distinction between them, but I’ve decided instead to start with induction and then go on to validity and truth next week and then look at deductive arguments and the evaluation of them in the final week. So we’re going to deal with induction this week. Oh, okay. Oh, I’ve done it now. I was going to ask you to tell me what an inductive argument was, but there we are. Okay. You knew this anyway, didn’t you? Yes. Good. Okay. There you go. Well, fantastic. Inductive arguments are such that the truth of their premises makes the truth of conclusion more or less likely. Okay and if you remember we looked at two examples in the first place we looked at the sun’s rising the sun has risen every day in the history of the world therefore the sun will rise tomorrow and every time you see Marianne she’s been wearing earrings so next time you see her she’ll be wearing earrings. I’m going to leave them off next week if I remember. All inductive arguments rely on the principle of the uniformity of nature as Hume called it, David Hume called it. And the only arguments for the principle of the uniformity of nature itself are themselves irrelevant.of nature itself are themselves inductive.

[译文 4]

今天我们要开始学习如何评估论证。现在，今天我本来打算从有效性和真值开始，讨论它们之间的区别，但我决定改为先从归纳开始，下周再讲有效性和真值，然后在最后一周讨论演绎论证及其评估。所以本周我们来处理归纳。哦，好吧。哦，我已经说出来了。我本来想请你们告诉我什么是归纳论证，但既然已经说了，那就算了吧。好的。反正你们本来就知道的，不是吗？是的。很好。好的。那就这样吧。嗯，太好了。归纳论证是这样的：其前提的真使得结论的真变得或多或少更有可能。好的，如果你还记得的话，我们一开始看了两个例子：我们看了太阳升起——太阳在世界历史上的每一天都升起了，因此太阳明天也会升起；以及每次你看到 Marianne，她都戴着耳环，所以下次你见到她时她也会戴着耳环。（如果我记得的话，我下周就不戴耳环了。）所有归纳论证都依赖于休谟——David Hume——所称的"自然齐一性原则"。而对"自然齐一性原则"本身的论证，本身也全都是归纳的。

[段 5]

So it looks as if any argument you offer for induction is going to be circular and based on induction itself. And this is a real problem. People would love to be able to justify the principle of the uniformity of nature, to say why we should believe that the future will be like the past, but no one’s conclusively succeeded. There’s reams and reams and reams of books and papers written on this problem. And there are lots of theories about it, but there’s no theory on which everyone would converge yet. Okay, different types of inductive argument. inductive generalizations, causal generalizations, arguments from analogy and arguments from authority, we’re going to have a look at each of these separately and look at how to evaluate them. So by how to evaluate, how to tell whether they’re good arguments or bad arguments. Because remember inductive arguments are not, it’s not a matter of either or with inductive arguments. They’re either strong or weak. Okay, so there’s a gradation. It’s a matter of degree as to how good an inductive argument is. Let’s start with inductive generalisations. What I mean by this is that the premise identifies the characteristic of a sample of the population, of a population, and the conclusionsof a population, and the conclusion extrapolates that characteristic to the rest of the population. And all inductive arguments are actually a form of this, of inductive generalization.

[译文 5]

因此看起来，你为归纳提供的任何论证都会是循环的，并建立在归纳本身的基础上。这确实是一个真正的问题。人们非常希望能证明"自然齐一性原则"，说明我们为什么应该相信未来会和过去一样，但没有人能够给出决定性的证明。关于这个问题已经写出了大量大量的书籍和论文。有很多相关的理论，但至今还没有一个所有人都能达成一致的理论。好的，归纳论证的不同类型：归纳概括、因果概括、类比论证和诉诸权威论证，我们将逐一考察它们，并学习如何评估它们。那么所谓"如何评估"，就是如何判断它们是好论证还是坏论证。因为请记住，归纳论证不是——归纳论证不是非此即彼的，它们要么强，要么弱。好的，所以是有一个程度的问题。一个归纳论证有多好，是一个程度的问题。让我们从归纳概括开始。我所说的归纳概括是指：前提识别了一个总体中某个样本的特征，而结论则将该特征外推到总体的其余部分。实际上，所有归纳论证都是归纳概括的一种形式。

[段 6]

So in learning how to evaluate inductive generalizations, you can apply everything you learn to other types of inductive generalization. But let’s have a look at them generally. Okay, here are two examples. so okay looking first at this one what’s the population that we’re looking at here so do you remember I said the premise points to a sample of a population and the conclusion extrapolates to the rest of the population so what do I mean by the population in this case voters exactly that’s right So we’re saying here that 60% of the voters have been sampled, and that 60% said they’d vote for Mr Many Promise. And we’re extrapolating from that to, therefore, actually there’s a suppressed premise here, isn’t there? Or there’s something we could add in here. That the sample has to be representative. Well, no, we’ll move on to that in a minute. we’re sort of assuming aren’t we that 60% of the population as a whole would be enough for him to win do you see what I mean?him to win. Do you see what I mean? Because that’s implied by this, isn’t it? Rather than actually stated. Okay, and then the other one we’ve got here, what’s the sample? Oh, Sorry, what’s the population here? One. The number of calls. One what? The number of calls. Calls to BT. Yep, calls to BT.

[译文 6]

所以在学习如何评估归纳概括时，你可以把你学到的所有东西应用到其他类型的归纳论证上。但让我们先大致看一下它们。好的，这里有两个例子。所以，好，先看第一个——我们这里考察的总体是什么？你还记得我说的，前提指向一个总体的样本，而结论则外推到总体的其余部分吗？那么在这种情况下，我所说的"总体"是什么意思？选民——没错，就是这样。所以这里我们说的是，有 60% 的选民被抽样调查，而这 60% 的人说他们会投给 Mr Many Promise 的票。我们由此外推，因此，实际上这里有一个被省略的前提，不是吗？或者我们可以在这里加一点内容。那就是样本必须是具有代表性的。好，不，我们等一下再讲那一点。我们是不是在某种程度上假设，总体中有 60% 就足以让他获胜，你明白我的意思吗？因为这是这句话所暗示的，不是吗？虽然并没有明确说出来。好的，然后我们这里的另一个例子，这里的样本是什么？哦，抱歉，这里的总体是什么？一是电话呼入的次数。什么一？电话呼入的次数。打给 BT 的电话。对，打给 BT 的电话。

[段 7]

So the premise says whenever I’ve tried to ring BT, whenever I’ve tried to make calls to BT, it’s taken me hours, and I’m extrapolating to that for that to… Actually, it’s calls by me, actually, isn’t it, rather than calls generally. So I’m extrapolating from my past experience to my future experience correctly. Okay, so what I want you is to have a look at each of these arguments, or you can choose just one of them if you want to do it more slowly, and write down the questions to which you would need answers in order to decide whether these are good arguments. And then we’ll go through them together. So have a look yourself and just think about these questions and think about what you would ask in order to satisfy yourself that these were good arguments. Okay.Okay, anyone want to give me examples of the sort of questions you would ask? On the first one I’d ask how big the population itself was. It could be ten people. Okay, if the electorate was just ten people, why would that help you evaluate the argument? Is it really the population, the number of the population you want, or what else might it be? the size of the sample. You might want to know the size of the sample. Yeah, yes, I thought you might. Because if you’ve got 10 people only were in the sample and yet there are a million people in the population, then the sample just isn’t big enough, is it?

[译文 7]

所以前提说的是，无论我什么时候尝试打给英国电信，无论我什么时候尝试打电话给英国电信，都要花上好几个小时，而我由此推断……其实，是我自己打的电话，对吧，而不是一般的电话。所以我是正确地从我过去的经历推断到我未来的经历。好的，那么我希望你做的就是逐一看看这些论证，或者如果你想慢一点，也可以只选其中一个，把你需要回答的问题写下来，以便判断这些是不是好的论证。然后我们会一起过一遍这些论证。所以你自己先看一下，想想这些问题，想想你会问些什么来说服自己这些是好的论证。好的。好的，有人想给我举几个你会问的问题的例子吗？对于第一个，我会问总体本身有多大。可能只有十个人。好的，如果选民只有十个人，那这怎么会帮你评估这个论证呢？你真正想知道的是总体、也就是总体的数量，还是别的什么呢？是样本的大小。你可能想知道样本的大小。是的，是的，我就猜到你会这么说。因为如果样本中只有10个人，而总体有100万人，那么这个样本就不够大，对吧？

[段 8]

Have you got another question? Well, only because I know from experience that just because you’re a voter who says you would vote for someone doesn’t mean you’ll actually vote. and so do you have to know what percentage of the people sampled are likely to vote? I mean, is it implicit in your word voters? No, it isn’t implicit in the word voters. Do you need to know how many of those sampled will actually vote? You might want to, yes. I mean, one of the things you would certainly want to consider here is that the voters sampled said that they would vote for Mr. whatever his name is, but actually won’t vote for him. He won’t vote at all?won’t vote for him or may not vote at all yes I mean either way it wouldn’t make much difference so yes I don’t think that’s yes that’s a bit of background information that you would bring to bear on this particular argument something you know about voters which show that you you really have to know a bit more about well you presume I bet it expects there’s a number by which they determine how many are likely to actually say, I don’t know. You’d certainly need to know whether they were telling the truth. Yes, you’d certainly need to know whether they were telling the truth, yeah.

[译文 8]

你还有别的问题吗？嗯，只是因为我从经验中知道，仅仅因为一个选民说他会投给某个人，并不意味着他真的会去投票。所以你是否需要知道样本中有百分之多少的人可能会真的去投票？我的意思是，这是否隐含在你的"选民"这个词中？不，“选民"这个词本身并不隐含这一点。你是否需要知道样本中有多少人真的会去投票？你可能想知道，是的。我的意思是，你当然会想考虑的一件事情是：被抽样调查的选民说他们会投给那位某某先生，但实际上他们不会投给他。他根本不会投票吗？不会投给他或者根本不会去投票，是的，我的意思是无论哪种情况都不会有太大区别，所以是的，我不认为……是的，这是你会用来评估这个特定论证的一点背景信息，你知道的一些关于选民的事情，这些事情表明你确实需要更多地了解……嗯，你猜我打赌你会期望有一个数字来确定他们实际上会说的概率，我不知道。你当然需要知道他们是否在说真话。是的，你当然需要知道他们是否在说真话，是的。

[段 9]

Okay, it’s certainly the case that Mr Many-Promises is not likely to win if he’s not going to stand, even if 60% of the voters… So actually that’s quite a good counter-example, isn’t it? A case where the premise would be true, but the conclusion would have to be false. That is quite a good counterexample to that. If you’ve got a situation where the voters really did want to vote for whoever it was, but he wasn’t going to stand. Yeah, I like that one. Another one here. Good. You’d want to know whether the sample is representative, wouldn’t you? Because if the only people they asked were males, then who knows what women are going to do. or if they’re all under 24 or if they’re all black or if they’re all whatever you needblack or if they’re all whatever you need to know that the sample chosen is representative of the population as a whole Yes, okay. So If you have something like the radio, there was a radio program wasn’t there that was taking votes for something or other and A lot of people so I mean actually what you want to do is you want to ask whether the premise here is true at all Yes, definitely. Yeah. Yes Yes, because it may be that 60% of the voters said that they would vote for Mr.

[译文 9]

好的，事实确实如此，如果"承诺先生"不参加竞选，他就不太可能获胜，即使有60%的选民……所以这其实是一个相当好的反例，对吧？这是一个前提为真但结论必须为假的情况。这对该论证来说确实是一个相当好的反例。如果你遇到这样一种情况：选民真的想投票给那个人，但他不参加竞选。是的，我很喜欢这个。再来一个。很好。你会想知道样本是否有代表性，对吧？因为如果他们只问了男性，那谁知道女性会怎么做呢。或者如果他们都是24岁以下的，或者如果他们都是黑人，或者如果他们都是无论什么——你需要知道，所选的样本是否代表了整个总体。是的，好吧。所以如果你有像广播这样的东西，有一个广播节目不是在为某件事投票吗，很多人……我的意思是你实际要做的是，你要问这里的前提是否真的为真。是的，绝对是的。是的。是的，是的，因为可能的情况是，60%的选民说他们会投票给那位先生。

[段 10]

Brown, but then something dreadful happens, and it’s certainly not the case that if you sampled them again just before the election, they would still say, good, you’re coming up with all sorts of things I haven’t got myself here. This is brilliant. Who did the sampling? Who did the sampling? Yep, that would be a very good thing. And again, I mean, that’s another example of is the premise true? because if the person saying that 60% of the voters said that they would vote for him, if they’re all apparatchiks for Mr Many-Promise who want to make him feel good before the election, you might question the premise itself, mightn’t you? OK, what about this one? Or is there anything that would be added to this one that we haven’t already considered? Gentleman there. When, I think, is perfectly good, because if I’ve been trying to ring BT at 2 o’clock in the morning, It mightring BT at 2 o’clock in the morning, it might be perfect. You know, yes, it may have taken hours, but were I to ring at 10 o’clock in the morning, it might be different. I’m assuming they don’t answer the phone at 2 o’clock in the morning. Okay, it’s certainly reasonable to ask whether it’s just me. Yes, I mean, there might be something about my particular telephone number, that whenever I ring BT, there’s something that says don’t answer this one or something like that.

[译文 10]

布朗先生，但随后发生了某件可怕的事情，可以肯定的是，如果你就在选举前再次对他们进行抽样调查，他们不会再说……好吧，你提出了各种各样的我自己没想到的东西。这太棒了。谁做的抽样调查？谁做的抽样调查？是的，那会是一个非常好的问题。再说一次，我的意思是，这又是另一个关于前提是否为真的例子。因为如果说60%的选民说他们会投票给他的人都是"承诺先生"的党羽，想让他在选举前感觉良好，你可能会质疑前提本身，对吧？好的，这个呢？或者对这个论证还有什么我们没考虑过的要补充的吗？那位先生。当，我认为，是完全没问题的，因为如果我一直试图在凌晨两点打给英国电信，它可能……在凌晨两点打给英国电信，它可能是完美的。你知道，是的，可能确实花了好几个小时，但如果我在上午十点打，可能就不一样了。我猜他们不会在凌晨两点接电话。好的，问问是否只是我个人的情况当然是合理的。是的，我的意思是，可能有一些关于我那个特定电话号码的情况，无论我什么时候打给英国电信，都有什么东西说不要接这个或者类似的事情。

[段 11]

But as the conclusion is that when I ring BT, do you see what I mean? Again, the way I’ve set this up, the population here is calls that I make to BT rather than calls that anyone makes to BT. Yes, I might have only made one or two. Again, that’s structurally the same as when we said here, how many people did we sample in the population? and what percentage of the population is that? And you’re suggesting exactly the same thing here quite properly. If I’ve only tried to ring once or twice, then, you know, is that really a big enough sample? Good. Again, you’re questioning whether that premise is true. I mean, maybe I’m just very bad at calculating time. Maybe I’m one of these people who’s very keen to get somebody to answer my phone call immediately and if it takes 30 seconds then I get very irritated and think it’s ours.irritated and thinks it’s ours. Okay, you would have to assume, wouldn’t it, that it was the same part of BT, again, because otherwise you’d get an equivocation, wouldn’t you? There’s BT here, wouldn’t mean the same as BT here, okay? An equivocation, by the way, is an argument in which you use the same word with two different meanings, okay? So if you think of the word bank, It could mean financial institution.

[译文 11]

但结论是当我打给英国电信的时候，你明白我的意思吗？再一次，我设置这个论证的方式是，这里的总体是我打给英国电信的电话，而不是任何人打给英国电信的电话。是的，我可能只打过一两次。再说一次，这在结构上和我们之前在这里说的是一样的，我们在总体中抽样了多少人？这占人口的百分之多少？你在这里恰当地提出了完全相同的事情。如果我只试过一两次，那么，你知道的，这真的是一个足够大的样本吗？好。再说一次，你在质疑那个前提是否真的为真。我的意思是，也许我只是非常不擅长计算时间。也许我是那种非常渴望立刻有人接电话的人，如果等了30秒我就会非常恼火，觉得花了很长时间……觉得花了很长时间。好的，你必须假设，对吧，是英国电信的同一个部门，因为否则就会出现歧义，对吧？这里出现的英国电信和那里出现的英国电信，意思不一样，对吧？顺便说一下，歧义是指在同一论证中你对同一个词使用了两种不同的含义，对吧？所以如果你想一下"bank"这个词，它可以指金融机构。

[段 12]

It could mean an action of an aeroplane or it could mean the side of a river. And if in an argument you used it in all three of those meanings, you could imagine an argument that would look good, but as a matter of fact, wouldn’t work at all. And that’s as a result of equivocation. You’re equivocating on the word bank. So if I were equivocating here on the word BT or the letters BT, my conclusion might not follow from my premises. Okay, very good. That really is good. I think it’s very impressive. You’ll see as I go through the things that I’m going to list that you’ve said just about all of them. Okay, firstly, is that just about all of them? There’s one I think I’ve got that you haven’t. Is the premise true? Okay, we’ve got 60% of the samples said that they would vote for Mr. Many Promise. Well can we really believe that? Might they be bad at record-keeping? So it actually wasn’t 60% it was only 50% and you know if youpercent, it was only 50 percent, and you know, if you, last year when you used those people, they were completely hopeless. Might they be engaged in wishful thinking? Might they be bad, just bad at maths, they can’t work out percentages? And am I telling the truth? Am I in the pay of one of BT’s rivals?

[译文 12]

它可以指飞机的动作，也可以指河岸。如果在一个论证中你在所有这三种含义上都使用它，你可以想象一个看起来不错但实际上根本行不通的论证。这正是歧义造成的。你是在"bank"这个词上做了歧义处理。所以如果我在"BT"这个词或"BT"这几个字母上做了歧义处理，我的结论可能就不会从我的前提中得出。好的，非常好。这真的很好。我觉得这非常令人印象深刻。当我接下来过一遍我要列出的这些东西时，你会发现你们说的几乎涵盖了所有。好的，首先，是不是几乎涵盖了所有？有一个我认为我有但你们没提到的。前提是否为真？好的，我们说有60%的样本说他们会投票给"承诺先生”。嗯，我们真的能相信这一点吗？他们会不会不善于记录？所以实际上不是60%而是只有50%，而且你知道，如果你，去年你用那些人的时候，他们完全不行。他们会不会在进行一厢情愿的想法？他们会不会很差，只是数学很差，不会算百分比？还有，我在说实话吗？我是不是在为英国电信的某个竞争对手工作？

[段 13]

Am I prone to exaggeration? Am I just very bad at estimating time? So lots of reasons why the premise itself might not be true. And if you remember, whenever we’re evaluating an argument, there are two things we’ve got to look at. Can you remember what they are? Just two basic things we look at whenever we’re evaluating an argument of any kind at all. One is, does the conclusion follow from the premises? That’s right. And the other is, are the premises true? That’s right. is if even one premise is false, then that doesn’t guarantee the truth of the conclusion, does it? Or doesn’t even make the truth of the conclusion more likely. So first thing you look at when you look at any argument is, are the premises true? Okay, how large is the sample? Again, you’ve got this. How many of those who would vote in the election were sampled? Ten out of one million? Well, that doesn’t look very good, does it? A thousand out of one million? That looks better. How many is enough, though, do you think? And that’s a really difficult question, isn’t it? How many is enough? I’m just speculating.is enough. I’m just specifying here that one million is the population. And then we’re saying, okay, how many of those would count as enough? And I’m saying there actually isn’t any answer to that.

[译文 13]

我是不是容易夸大其词？我是不是非常不擅长估计时间？所以有很多理由说明这个前提本身可能并不成立。还记得吧，每当我们评估一个论证时，有两件事是我们必须看的。你能记得是哪两件事吗？任何形式的论证我们评估时都会看两个基本方面。一是，结论是否由前提推出？没错。另一个是，前提是否为真？没错。只要有一个前提为假，那就不能保证结论为真，对吧？甚至也不会让结论更可能为真。所以当你看任何论证时，你首先要看的就是，前提是否为真？好，样本有多大？再来一次，你已经知道了。被抽样调查的人占参加选举投票人数的比例是多少？一百万人里抽十个？嗯，这看起来不太好，对吧？一百万人里抽一千个？那看起来好一些。不过你认为多少才算够呢？这真是一个很难的问题，对吧？多少才算够？我只是猜测。is enough. 我只是在这里说明一百万是总体。然后我们在说，好，这当中多少人算够呢？我在说，实际上这个问题没有任何答案。

[段 14]

We can certainly answer that 10 is probably not enough. And we might be able to say that 990,000 or 1,000 or 10,000, I don’t even know how much a million is, a thousand thousand isn’t it? 900,000 would be enough, okay, but in between those two numbers what counts as enough? Well that’s coming later, that’s coming when we look at the representativeness of the sample at the moment, the only thing we’re talking about is the size of the sample, if I say all swans are white and you say well what’s your reason for saying that and I say well I saw a swan just now and it was white and you say what just one and I say yeah and you can be more or less inductively bold and actually if we were to look at people in this room if we were to do a head count of people in this room we’d find that some of us are very well actually I shouldn’t say us because I’m not inductively bold but some of us would be prepared to extrapolate from a very small number and others of us would be very skeptical about extrapolating even from quite a large numberabout extrapolating even from quite a large number. So actually the question how many is enough, the answer would be it depends on who you are and on how inductively bold you are.

[译文 14]

我们当然可以说十个很可能不够。我们也许可以说 99 万，或者 1,000，或者 10,000，我甚至不知道一百万是多少，一千个一千对吧？90 万就够了，好，但在这两个数字之间，多少才算够呢？嗯，那个以后再讲，那要等到我们看样本的代表性时再讲。现在我们只在讨论样本的大小，如果我说所有天鹅都是白的，你说那你有什么理由这么说，我说嗯我刚刚看到一只天鹅它是白的，你说什么就一只吗，我说对，你可以或多或少地在归纳上大胆一些，实际上如果我们看看这个房间里的人，如果我们数一下这个房间里的人，我们会发现我们当中有些人其实非常……我应该说"我们当中"因为我自己并不归纳大胆，但我们当中有些人会愿意从很小的样本进行推广，而另一些人对即使从相当大的样本进行推广也会非常怀疑，对推广表示怀疑，对吧？所以实际上多少才算够这个问题，答案会是这取决于你是谁，取决于你在归纳上有多大胆。

[段 15]

Well statisticians have to come up with something that they would count as enough. But a confidence range. Yeah. And the larger the sample, the smaller the confidence range. They can be more confident. I think it’s a representative. When you say the larger the sample, do you mean that it’s certainly true that if 1,000 have been sampled, that’s much more confidence boosting than 10? No, it’s not. That’s what you mean? Yes. Yes, OK. Are they saying, as a result, that 80% in the election will vote one way, plus or minus 2%, or are they saying 55% plus or minus 10%? And the range of their prediction depends upon the size of the sample. No, I’m getting out of my depth here. I don’t understand what you’re saying, I’m afraid. There’s quite a good example from history on this, which was an American election in 19… Yes, we’re coming to that. That’s represented.Yes, we’re coming to that. That’s representativeness. So, you know, it’s not the absolute size. That’s of less importance than the actual representativeness. No, let’s leave representativeness aside. At the moment I’m just talking about size. All we need to look at is how many of those in the sample, how many in the population, how many in the sample, do we think that we’ve got enough who’ve been sampled in order to make us more confident about the extrapolation.

[译文 15]

嗯，统计学家必须拿出某种他们认为算够的标准。但是一个置信区间。对。而且样本越大，置信区间就越小。他们可以更有信心。我认为这是代表性。你说样本越大，你是说如果抽了 1,000 个，那肯定比抽 10 个更让人有信心，对吗？不，不是的。你是这个意思吗？是的。是的，好。他们是在说，因此选举中会有 80% 的人投票给某一方，正负 2%，还是说 55% 正负 10%？他们的预测区间取决于样本的大小。不，我说到这里就有点超出我的能力范围了。恐怕我不太明白你在说什么。历史上有一个关于这个的很好的例子，是 19……年的一次美国选举。是的，我们马上要讲到那个。那是代表性。是的，我们马上要讲到那个。那就是代表性。所以，你知道，关键不是绝对的大小。那其实没有实际代表性那么重要。不，我们先不谈代表性。现在我只是在谈大小。我们只需要看的是，样本中有多少人，总人口中有多少人，样本中有多少人，我们是否认为我们抽到了足够多的人从而能对推广更有信心。

[段 16]

If I’ve only rung BT once, then my claim that the next time I’m going to ring is really pretty low, isn’t it? It’s a very weak argument. Whereas if I’ve rung BT 50 times and not got through, then that’s more reason to think. So if we think, remember that inductive arguments make the premises make the conclusion more or less likely. Well, if my premise is I’ve rung BT once in the past and it took them hours to answer, then so it’ll take them hours to answer again. My argument is much less strong than if I say I’ve rung BT 50 odd times in the past and it’s taken them hours to answer. Therefore, it’ll take them hours to answer next time. See what I mean? and again here if I say 10 out of what 60% of 10 in other six voters out of a million said that they’d be voting for mr. many promise therefore mr. many promise will win thepromise therefore mr. many promise will win the election that’s a less good argument a weaker argument than if I say 60% of a thousand voters say that they’ll vote for mr. many promise therefore mr. many promise will 60% of people will vote for him in the election and he’ll win see what I mean we haven’t actually looked at representativeness yet we will about to do so look you’re We’re all dying to get on to unrepresentativeness, so let’s do so.

[译文 16]

如果我只给 BT 打过一次电话，那么我说下次我打电话会等很久，这个主张的依据就相当薄弱，对吧？这是个非常弱的论证。而如果我给 BT 打了 50 次电话都没打通，那就有更多的理由这样想。所以大家想想，记得归纳论证使前提使结论更可能或更不可能成立。那么，如果我的前提是我过去给 BT 打过一次电话，等了好几个小时才有人接，所以下次也会等好几个小时。我的论证就远不如我说我过去给 BT 打过 50 多次电话，每次都等好几个小时才有人接。因此，下次也会等好几个小时那么强。明白我的意思吗？同样在这里，如果我说一百万选民中抽 10 个人——也就是 10 的 60% 即 6 个选民——说他们会投给 many promise 先生，因此 many promise 先生会赢得选举——这是不好的论证，比不上我说一千个选民中有 60% 说他们会投给 many promise 先生，因此选举中会有 60% 的人投给他，他会赢。明白我的意思吗？我们其实还没看代表性，我们马上要看，看，你们所有人都迫不及待地想讲非代表性，那我们就开始吧。

[段 17]

Here we go. Okay, the second thing that we ask is how representative is the sample? What you should do, incidentally, I’m giving you, again, you might see it as another algorithm, another just list of steps that you might do. Again, try and keep them separate in your mind, because if you tick off each one, okay, you’ve asked yourself how many there are in the sample and how many there are in the population, and made a judgment about whether there is enough in the sample to be able to extrapolate. Second question you ask is whether the sample is representative. See what I mean? Descartes, a very famous philosopher, brilliant philosopher, had a list of rules of thinking. And one of the things he said was that you should take any problem you have and break it up into its parts and then deal with each part separately. And then make sure that looking at each of the parts you can put together as a solution to the whole. And what I’m suggesting here is you ask each of these questions separately so that you make sure that you ask allseparately so that you make sure that you ask all of them. And it just makes your thoughts clearer. Again, as with first you identify the argument and analyse it, then you evaluate it. Okay, you don’t try and do both at once.

[译文 17]

我们开始。好，我们问的第二件事是样本的代表性如何。顺便说一下，你应该做的，我再次给你提供，你可以把它看作另一个算法，另一个你可能采用的步骤清单。同样，尽量在头脑中把它们分开，因为如果逐个打勾，好，你已经问过自己样本中有多少、总体中有多少，并对样本是否足够多以能够进行推广做出判断。你问的第二个问题是样本是否具有代表性。明白我的意思吗？笛卡尔，一位非常著名的哲学家，非常杰出的哲学家，他有一份思维规则清单。他说过的一件事是，你应该把你面临的任何问题分解成各个部分，然后分别处理每个部分。然后确保看过每个部分之后你能把它们整合起来作为对整体的解答。而我在这里建议你分别问每个问题，这样你就能确保你问了所有问题，分别问每个问题以确保你问了所有问题。这会让你的思路更清晰。同样，就像首先你识别论证并分析它，然后你评估它。好，你不要试图同时做两件事。

[段 18]

Okay, so here, again, you’ve got all these. Were the voters sampled all female? Well, I mean, there are a lot of medical experiments or medical surveys that look only at men and then extrapolate the results to women. I don’t know if you’ve seen recently, they’ve decided that for women, the symptoms of a heart attack are quite different from the heart attack symptoms of a man. And therefore, all the extrapolation that they’ve done in the past from male experience of heart attacks to female experience of heart attacks has been faulty. There was quite a big thing about that a couple of weeks ago. Are they all over 40? Are they all white? Are they all middle class? Are they all known to the person conducting the survey? The famous example that you were mentioning a minute ago, and in fact that you’ve just mentioned as well, in an election between who, Roosevelt and Landon, that’s right, they thought that 60% of the population was going to vote. That’s what their sample have said. But how did they find the sample? They looked in the telephone book. How many people had telephones then? actually very few. So althoughthen? Actually very few. So although there was 60% of the sample said that they would vote for Roosevelt, actually the sample was horrendously unrepresentative because it was middle class people with a fair amount of money who had telephones and therefore it didn’t represent the population as a whole.

[译文 18]

好，所以这里，同样地，你面对所有这些。被抽样的选民全都是女性吗？嗯，我的意思是，有大量的医学实验或医学调查只研究男性，然后把结果推广到女性。我不知道你最近有没有看到，他们已经认定对女性来说，心脏病的症状与男性的心脏病症状差别很大。因此，过去所有从男性的心脏病经历推广到女性心脏病经历的推广都是有缺陷的。几周前关于这个有相当大的讨论。他们全都超过 40 岁吗？全都是白人吗？全都是中产阶级吗？全都是进行这项调查的人认识的人吗？你刚才提到的那个著名例子，事实上你也刚刚提到过，在一场选举中，候选人是——罗斯福和兰登，对，他们以为会有 60% 的人口去投票。这就是他们的样本所说的。但他们是怎么找到样本的呢？他们查了电话簿。那时候有多少人有电话？实际上非常少。所以虽然样本中有 60% 的人说他们会投给罗斯福，实际上这个样本极其不具代表性，因为那是有一定资产的中产阶级人才有电话，因此它并不代表整体人口。

[段 19]

Okay and anyway the same thing here again we came this have I only around BT on a Sunday after 10 p.m. when I’m in a hurry, etc., etc. Okay, so firstly, is the premise true? Secondly, what was it, how large is the sample as a percentage of the population? Thirdly, how representative is the sample? Three questions to ask there. Here’s another one, here’s a one you haven’t thought of and perfectly reasonable that you shouldn’t. If you were asked, here are two hands of cards, which one is most likely to come up? Who thinks this one is most likely to come up? No? Okay, who thinks this one is most likely to come up? Oh, you’re all very clever, aren’t you? You’re absolutely right. They’re actually equally likely to come up because, of course, cards are just at random. They’re not, but actually, if you ask the students at the university where this experiment was done, which hand is likely to come up, they come up overwhelmingly, overwhelminglythey come out overwhelmingly against this one and for this one. This is much more likely to come up than this one. Now, you can see why they think this, can’t you? Can you? This is the one they’d love to have come up, and this is the one that they have come up, they think, all the time, sort of thing.

[译文 19]

好的，反正这里也是一样，我们这次过来是在星期天晚上十点之后，我赶时间的时候等等等等。好了，首先，前提是真的吗？其次，样本量占人口的比例有多大？再次，样本有多大的代表性？这里有三个问题要问。还有一个，是你们没想到的，但其实很合理，你们不应该没想到。如果有人问你，这里有两手牌，哪一手更可能赢？谁觉得这一手更可能赢？不觉得？好的，谁觉得这一手更可能赢？哦，你们都好聪明啊，是不是？你们完全正确。它们其实赢的概率是相等的，因为当然，纸牌是随机的。它们其实不是，但如果你问进行这个实验的那所大学里的学生，哪手牌更可能赢，他们绝大多数，绝大多数——他们压倒性地反对这一手，而支持这一手。这一手比这一手更可能赢。你们能看出他们为什么这么想吧？能吗？这一手是他们想要的，这一手是他们认为一直在出现的那种。

[段 20]

But, of course, actually it doesn’t quite work like that because they’re using an informal heuristic to say, in my experience this never comes up and this always comes up and actually you just can’t use that here can you because what comes up is something like that but certainly not that it just means a way of making a decision okay a rule of thumb if you like a way of making a decision thank you for asking I should have explained it before okay so so if an inductive generalization is based on an informal claim like this, in my experience, hands like this never come up. Therefore, this one is much less likely than that one. Then you should be very wary of the generalization. And here’s another one. And I expect you’re all going to be clever enough to get this too. Okay, in four pages of a novel, how many words would you expect to find ending in ing and in four pages of a novelan ing, and in four pages of a novel, how many words would you expect to find that include the letter n? Would you expect that to be larger than that, or vice versa? So you’d expect more of the ing words. No, more of the n words. Put up your hands if you think there are more n words.

[译文 20]

但当然，实际上情况并不完全是这样，因为他们用的是一个非正式的启发法来下判断，根据我的经验，这一手从来不出现，而这一手总是出现，而你其实根本不能在这里这么用，对吧，因为出现的会是类似这样的牌，但绝不是那种。这只是意味着一种做决定的方式，好吧，如果你愿意，可以叫做经验法则，一种做决定的方式，谢谢你提问，我应该之前就解释清楚的。好了，那么如果一个归纳概括是基于这样的非正式说法——根据我的经验，像这样的牌手从来不会出现，所以这一手比那一手出现的可能性要小得多——那么你就应该对这个概括非常警惕。还有一个。我估计你们也都够聪明，能回答出来。好了，在小说的四页中，你预计能找到多少个以 ing 结尾的词？在小说的四页中，你预计能找到多少个包含字母 n 的词？你会认为哪个更多，还是反过来？所以你会觉得 ing 词更多。不，n 词更多。如果你认为 n 词更多，请举手。

[段 21]

Okay, put up your hands if you think more ing words. Okay, that’s interesting. This time you have fallen for the trick. Because, of course, there are going to be N-words, because there’ll be N-words that aren’t in-words, but there won’t be in-words. That’s right. They’re always going to… Oh, okay, I’m sorry. So you’re absolutely right. There are going to be many more N-words than there are in-words, because there are going to be at least as many N-words as there are in-words. Yes. Okay. Sorry, you did get that. What happens again when you ask these students, the psychology students at the university where this experiment was done, is they expect many more of these because they can think of many more ing words than they can of n words. And therefore, they inductively generalize again. Well, I can think of many more of those. Therefore, there probably are more of those. Again, bad arguments. If I ask you how many footballers or something from a particular team score well.from a particular team score well, you’ll be able to think, well, actually, that’s a very bad example. Anything that you think you know a bit about, you’re probably tempted to rely on your own experience to make an inductive generalisation. That can work if you really do know what you’re talking about, but it doesn’t work if you’re just using that way of doing it on another context where actually your knowledge is not so secure.

[译文 21]

好的，如果你认为 ing 词更多，请举手。好的，有意思。这次你们中招了。因为，当然，会有 n 词，因为会有不是 ing 词的 n 词，但却不会有不是 n 词的 ing 词。没错。它们总是会……哦，好吧，抱歉。所以你们完全正确。n 词会比 ing 词多得多，因为 n 词至少会和 ing 词一样多。是的。好吧。抱歉，你们确实答对了。当你再去问那些学生，也就是进行这个实验的那所大学里的心理学学生的时候，会发生什么呢？他们预期这些词会多得多，因为他们能想到的 ing 词比 n 词多得多。于是他们再次进行归纳概括。嗯，我能想到的那种词更多。所以那种词可能就更多。同样是糟糕的论证。如果我问你，某支球队有多少足球运动员之类的问题，表现不错。某支球队的表现不错，你会想到，嗯，实际上那是个很糟糕的例子。任何你觉得了解一点的东西，你很可能就会倾向于依赖自己的经验来做一个归纳概括。如果你确实了解你在谈论的东西，这或许行得通，但如果在另一个语境里你的知识并不那么可靠，你只是用这种方法，那就行不通了。

[段 22]

Okay, so five steps there, I think it was. When you’re evaluating any inductive generalization, you’re looking for, firstly, is the premise true? Secondly, does the sample size of the population, is it large enough compared to the population as a whole? thirdly is the sample representative or is there a bias in it due to whatever all sorts of reasons for different biases and finally is it based on on an informal heuristic that actually an informal rule of thumb that actually just won’t stand up to proper scrutiny here okay and as i said all inductive general all inductive arguments are based on inductive generalizations and so that little way of testing things can be used for all of them let’s look at causal generalizedfor all of them. Let’s look at causal generalizations. Okay, a causal generalization is a type of inductive generalization. The premise identifies a correlation between two types of events and the conclusion states that events of the first type cause events of a second type. So the idea is that if you see A and B, A and B, A and B, A and B, A’s and B’s are always correlated, you extrapolate to the claim that A’s and B’s will always be correlated and you imply that the reason for this is that there’s a causal relation between them. So where there’s correlation there’s cause, that’s what a causal generalization is.

[译文 22]

好的，我想有五个步骤。当你在评估任何归纳概括的时候，你要看的是：第一，前提是真的吗？第二，样本量相对于总体来说足够大吗？第三，样本具有代表性吗，或者由于各种各样的原因存在某种偏差？最后，它是基于一种非正式的启发法吗？实际上是一种经不起严格审视的非正式经验法则？好的，正如我所说，所有归纳论证——所有归纳论证都是基于归纳概括的，所以这种检验方法可以用于所有归纳论证。让我们来看看因果概括。好的，因果概括是归纳概括的一种类型。前提识别出两类事件之间的相关性，而结论则声称第一类事件导致了第二类事件。所以这个想法是，如果你看到 A 和 B，A 和 B，A 和 B，A 和 B，A 和 B 总是相关的，你就推断说 A 和 B 总是会相关，并且你暗示之所以如此是因为它们之间存在因果关系。所以有相关就有因果，这就是因果概括的意思。

[段 23]

So let’s have a look at a couple. Okay married men live longer than single men therefore being married causes you to live longer. I apologize for this one. When air is allowed into a wound, maggots form. Therefore, maggots in wounds are caused by air being allowed into the wound. Sorry. Okay, I’ll tell you what, let’s do it openly. What do we need to know to know whether these arguments are good arguments? Okay, let’s have a look. Again, we ask, is the premise true? Who says married men live longer? Married men, a woman who wants to get married, Fred whose parents split up when he was five. Iwhose parents split up when he was five? I mean, who’s saying this? Where are we actually getting this information from? Who says maggots form when air gets into the womb, just as you said at the back there? Was it a newly qualified nurse who’s observed this once? Was it an elderly doctor who’s seen it a lot, but only in his own experience and in his own study, perhaps? Or was it a scientific study, one that you would expect to have looked more carefully? causation is actually to give you a little bit of background on this David Hume the person I’ve mentioned already in connection with the principle of the uniformity of nature believes that actually causation we cannot determine causation if we find A causes B and we try and find out why A causes B what is this causal relation what is it that relates the two things that are cause and effect, we’ll just find another correlation, C and D.

[译文 23]

让我们来看几个例子。好的，已婚男性比单身男性活得更久，因此结婚会让你活得更久。我为这个例子道歉。当空气进入伤口时，蛆就生成了。因此，伤口里的蛆是由进入伤口的空气引起的。抱歉。好了，这样吧，我们公开讨论。我们需要知道什么才能判断这些论证是不是好的论证？好的，我们来看一下。同样，我们要问，前提是真的吗？谁说已婚男性活得更久？已婚男性、想结婚的女性、五岁时父母离异的 Fred。什么？我五岁时父母离异？我是说，是谁在说这个？我们到底是从哪里得到这个信息的？谁说空气进入伤口蛆就会生成，就像你刚才在后面说的那样？是一个刚拿到资格的护士观察到一次这种情况吗？是一个老医生见过很多次这种情况，但也只是凭他自己的经验和在他自己的研究中吗？还是一项科学研究——那种你可以期待它做了更细致考察的研究？因果关系，我给你讲一点背景知识。我之前提到过的 David Hume，他在与自然齐一律相关的讨论中提到，他实际上认为我们不能确定因果关系。如果我们发现 A 导致 B，然后试图找出 A 为什么导致 B，这种因果关系是什么，是什么把这两个作为原因和结果的东西联系起来的，我们只会找到另一个相关关系 C 和 D。

[段 24]

Okay, so why do we think C and D are correlated? We look further and we look down and we see yet another correlation. So all we ever see is correlation. We never actually see the causal relation itself. We can never get to the causal relation itself. and he actually thought arguably, this is a very popular theory of Hume, although lots of people deny it these days that he actually thought causation didn’t exist at all, that causationhe thought causation didn’t exist at all, that our beliefs about causation are just a habit of mind. So we see A correlated with B, A correlated with B, A correlated with B, and we start to say that A causes B, and all we mean by that is that A is correlated with B. There’s just a constant conjunction between A and B. There’s nothing that makes A cause B. I have to say that there’s another theory of Hume’s that he says that A causes B where, had it not been the case that A, it would not have been the case that B. Had it not been the case that A, it would not have been the case that B. And that suggests that there’s a power of some kind, isn’t there, that makes A cause B. But we don’t ever see that power, do we? We just see the cause and the effect and a correlation between them.

[译文 24]

好的，那为什么我们认为 C 和 D 是相关的呢？我们进一步往下看，又看到另一个相关关系。所以我们看到的始终只是相关。我们其实从来就看不到因果关系本身。我们永远无法触及因果关系本身。而他实际上——可以说，这是 Hume 一个很流行的理论，尽管如今很多人否认它——他实际上认为因果关系根本不存在，他认为我们对因果关系的信念只是一种思维习惯。所以我们看到 A 与 B 相关，A 与 B 相关，A 与 B 相关，于是我们开始说 A 导致 B，而我们对这句话的全部意思不过是 A 与 B 是相关的。A 和 B 之间只存在一种恒常的联结。并不存在什么让 A 导致 B 的东西。我得说一下，Hume 还有另一种理论，他说 A 导致 B，意思是如果不是 A 出现了，B 就不会出现。如果不是 A 出现了，B 就不会出现。这暗示着存在某种力量，让 A 导致 B。但我们从来都看不到这种力量，对吧？我们只是看到原因和结果，以及它们之间的相关。

[段 25]

And so causation is a really interesting philosophical issue. The question what causation is, is endlessly interesting. I think it’s endlessly interesting. But it remains to be the case that our evidence for causation is always a correlation. But a correlation simply isn’t sufficient as evidence for causation, is it? Because it could be evidence for identity, for example. So night, well, the evening star goes down, the morning star…goes down, the morning star rises and so on and so forth, do they cause each other to do it? No, actually they’re the same thing. That’s why they’re correlated. That’s why the pattern is uniform. Do husbands cause wives? But they’re correlated. Well, what we’re saying is that correlation isn’t sufficient for a causation, but it’s the only evidence we’re ever likely to have. but when you see a causal generalisation it will be based on correlations but what we’re alerting you to here is that a correlation isn’t sufficient for a causation you need to ask lots of other questions so is the premise true? How strong is the correlation? How many married men were observed? I mean this is again exactly the same as how many are in the sample from the last question. How long were they observed? Were unmarried men observed? how many cases of maggots forming were observed because John Stuart Mill, famous philosopher English philosopher, came up with what he called the method of agreement and the method of difference for scientific experiments if you’re trying to work out what causes what you need to see firstly that they do correlate that the cause correlates with the effect Next thing you need to do is to try and bring about the cause without the effect.

[译文 25]

因此因果关系是一个十分有趣的哲学问题。“因果关系是什么"这个问题，永远都令人着迷。我认为它永远都令人着迷。但情况依然是：我们对因果关系的证据永远是相关性。然而相关性作为因果关系的证据是不够的，对吧？因为它可能只是同一性（identity）的证据。例如，夜晚，昏星落下，晨星……落下，晨星升起，等等，它们彼此之间是因果关系吗？不是，实际上它们是同一个东西。这就是它们具有相关性的原因。这就是为什么这种模式是统一的。是丈夫导致了妻子吗？可它们是相关的。我们这里要说的是，相关性不足以构成因果关系，但它是我们唯一可能拥有的证据。当你看到一个因果概括时，它一定建立在相关性之上，但我们在这里提醒你注意的是，相关性不足以构成因果关系——你还需要问很多其他问题：前提是否为真？相关性的强度有多大？观察了多少已婚男性？我是说，这和上一道题中样本里有多少人是完全一样的。他们被观察了多长时间？是否也观察了未婚男性？观察到了多少蛆虫生成的情况？因为 John Stuart Mill，这位著名的英国哲学家，提出了他所谓的"契合法"和"差异法”，用于科学实验——如果你想弄清楚什么导致什么，首先你需要看到它们确实相关，原因与结果相关；接下来你需要做的是尝试在没有结果的情况下引发原因。

[段 26]

Because if you’re saying that…without the effect. Because if you’re saying that A’s cause B, because A’s are always correlated with B, then what you do is you try and bring about an A without a B, because if you can do that, you’ve disproved your claim about causation. See what I mean? And that shows us that we tend to think that a cause is sufficient for its effect. That if A causes B, the occurrence of an A must be followed by the occurrence of a B, because A is sufficient for B. So that’s the method of samenesses and the method of differences, which tells you whether something’s a cause or not. Also, you want to ask, does the causal relation make sense, or could it be accidental? Let’s say that we discovered that in the whole history of the universe, every time a match has been struck, a pineapple has fallen. okay we have a correlation and we’ve done our very best to try and make sure that we’ve struck matches without a pineapple falling and it could keep on doing it um so we can’t break the correlation in any way do we think that matches striking cause pineapples to fall well some people are quite inductively bold here they they think yes if you’ve got a correlation as strong as that it must be causal.

[译文 26]

因为如果你在说……没有结果的情况下。因为如果你在说 A 导致 B，因为 A 总是和 B 相关，那么你要做的就是尝试造成一个 A 而不出现 B，因为如果你能做到这一点，你就推翻了你关于因果关系的论断。明白我的意思了吗？这表明我们倾向于认为原因是其结果的充分条件。也就是说，如果 A 导致 B，那么 A 的发生之后必然跟随着 B 的发生，因为 A 对 B 而言是充分的。这就是契合法和差异法，它可以告诉你某物是否是原因。此外，你还要问：因果关系是否讲得通，还是可能只是巧合？假设我们发现，在整个宇宙的历史中，每一次划着火柴，都会有一个菠萝掉下来。好，我们得到了一种相关性，而且我们尽了最大努力尝试在不让菠萝掉下来的情况下划火柴，而它可能一直是这样……所以我们无论如何都无法打破这种相关性。我们会认为划火柴会导致菠萝掉下来吗？有些人在归纳上确实相当大胆，他们认为是的，如果你得到一种如此强的相关性，那它一定是因果性的。

[段 27]

Apparently there’s also a correlation between the length of skirts and thea correlation between the length of skirts and the Dow Jones index as one goes up the other goes up and as one goes down the other goes down it might be the other way around but anyway there’s a correlation here do we think that the length of skirts causes the rise and fall of the Dow Jones index or vice-versa you can sort of see something that makes sense can’t you in that because maybe when the Dow Jones Index is really high, people are really excited and pleased, and therefore they’re risk-taking, so they put on their miniskirt. Okay, so the claim that being married makes you live longer if you’re a man. Why would being married cause men to live longer? I think this is where your claim about are we including civil relationships is quite interesting. Why would being married cause men to live longer? Incidentally, I think it causes women to die earlier. Just a warning to women in this room. Because they’re happier and reduce their stress. Okay, they’re happier, their stress reduces. Another explanation? They feel better. What? That’s a first, he says. It might also be because women tend to look after diets and things like that more. Men are cooked for more often than women are, perhaps. and when women do the cooking they’re concerned about nutrition and da-da-da-da so when a married man eats heand da-da-da-da, so when a married man eats, he tends to eat more healthily than a…

[译文 27]

显然，裙子的长度和道琼斯指数之间也存在一种相关性——裙子长度和道琼斯指数之间存在一种相关性——一个上升，另一个也上升；一个下降，另一个也下降，也可能是相反的方向，但无论如何这里存在一种相关性。我们会认为裙子的长度导致了道琼斯指数的涨跌吗？反过来呢？你能不能看出某种讲得通的解释——也许当道琼斯指数很高的时候，人们非常兴奋、非常高兴，因此他们敢于冒险，于是穿上迷你裙。好，那么关于"结婚会让男人更长寿"这一主张。为什么结婚会导致男人更长寿？我觉得你关于"我们是否包括民事伴侣关系"的说法很有意思。为什么结婚会导致男人更长寿？顺便说一句，我认为它会让女人死得更早。只是提醒一下在座的女士。因为她们更快乐，压力也减少了。好，她们更快乐，压力减小了。还有其他解释吗？她们感觉更好了。什么？这是头一次听到，他说。也可能是因为女性往往更注意饮食之类的事情。男人被做饭的频率比女人更高，可能吧。而且当女人做饭时，她们会关注营养，等等等等，所以当一个已婚男人吃饭时……等等等等，所以当一个已婚男人吃饭时，他往往吃得比……更健康。

[段 28]

I mean, we can think of reasons for why that would be the case, can’t we? So it’s not a complete mystery. What about this one? Why would air getting into a wound cause maggots to form? So, I mean, the experiment we’ve done here, some nurses seen that when a wound was covered up by accident or something like that, maggots didn’t form. and she thinks, well, could it be? So she covers up a few and she leaves a few open and she sees that the ones she’s covered up don’t get maggots, whereas the ones that are left open do get maggots. So she’s formed a hypothesis. Could it be that air getting into the wound causes maggots? But why would that be the case? Perhaps because there’s something carried in the air that causes maggots to form and actually we know now that that is the case. So, OK, so does the causal relation make sense? Incidentally, if it doesn’t make sense, does that mean it’s not causal? No, it doesn’t actually, does it? Because you can imagine that there may be something that is a complete mystery for us for a while. And I wish I could think of an example, but which turns out to be true and turns out to have an explanation. but even so if you can’t if it just if the things seem to be just totally disparate that would be a mark against this argument being a goodwould be a mark against this argument being a good one.

[译文 28]

我的意思是，我们能想到为什么会是这样的原因，不是吗？所以这并不是一个完全的谜。这一个呢？为什么空气进入伤口会导致蛆虫形成？那么，我意思是，我们在这里做的实验是，一些护士看到当伤口被意外覆盖或类似情况下时，蛆虫并没有形成。她就想，嗯，会是这样吗？于是她把一些伤口盖住，留一些敞着，她发现她盖住的那些没有长蛆，而敞着的那些长了蛆。于是她形成了一个假设：会不会是空气进入伤口导致了蛆虫？但为什么会是这样呢？可能是因为空气中携带着某种东西导致了蛆虫的形成，而现在我们知道确实如此。所以，好，那么因果关系讲得通吗？顺便说一句，如果它讲不通，那是否就意味着它不是因果关系？不，实际上不是，对吧？因为你可以想象，有些事情可能对我们来说在一段时间内完全是个谜。我希望我能想到一个例子，但事实上它最终被证明为真，并最终得到了解释。但即便如此，如果你不能——如果事情看起来完全不相干，那这就是反对这个论证的一个依据——反对这个论证是一个好论证的标志。

[段 29]

And we also might, and we’ve done this a bit, okay, what causes what? Could it be that being long-lived causes marriage? So it might be that having genes for longevity cause men to get married. So you said socioeconomic factors, but I’m suggesting it could be genetic factors. So there’s one set of genes such that if a man has them, he’s both more likely to get married and he’s more likely to live longer. So there’s one common cause for the two things rather than one thing causes the other. Yeah, and that’s, I couldn’t think of anything. Could maggots forming cause the air to get into the womb? No, I couldn’t think about that. So, okay, right, that, so that’s looking at causal generalizations and you’ll see that many of the questions that you would ask about causal generalizations are also questions you’ve already asked about inductive generalizations. That’s not surprising because causal generalizations are a type of inductive generalization and all the ones that you’re asking separately are the ones that say you know why should we think that a correlation has a causal relation under it so that so just moving on quickly to analogy here another type of inductive generalizationAnother type of inductive generalization, it takes just one sample of something and then extrapolates from a character of that example to the character of something similar to that thing and there’s a famous argument from analogy the universe is like a pocket watch, pocket watches have designers therefore the universe must have a designer and I think we’re probably all familiar with that argument.

[译文 29]

我们可能也已经做了一些，好，什么导致什么？会不会是长寿导致了婚姻？所以可能是拥有长寿基因的男性更容易结婚。你提到过社会经济因素，但我想提出可能是遗传因素。有一组基因，如果一个男性拥有它们，他既更可能结婚，也更可能长寿。所以这两个事情有一个共同的原因，而不是一个事情导致另一个。是的，那个，我想不出什么。蛆虫的形成会导致空气进入子宫吗？不，我想不到。好，好，那个，那就是在审视因果概括，你会看到你关于因果概括会问的许多问题，也是你已经就归纳概括问过的问题。这并不令人惊讶，因为因果概括是一种归纳概括，而你们单独在问的那些都是：为什么我们应该认为相关性背后存在因果关系？所以——所以快速进入类比——另一种归纳概括。另一种归纳概括，它只取某一个事物的一个样本，然后从那个例子的某个特征推断到与该事物相似的另一个事物的特征。这里有一个著名的类比论证：宇宙像一块怀表，怀表有设计者，因此宇宙必定有设计者。我想我们可能都很熟悉那个论证。

[段 30]

Okay, how would we go about questioning this argument? Yes, okay, what aspect are we picking out here and saying is similar to the two cases? So why is the universe like a pocket watch? I mean, using this famous example, what did the person believe? It was a very complicated elaborate. That’s what the person would say. That’s right, it was very… Who was it? It’s gone completely… Paley. That’s right, thank you. I’m sorry, I have got a head full of cotton wool, it’s very strange. Yeah, Paley believed that the pocket watch moves regularly, it’s very complex, it must have been very difficult to put together, and he believes that the universe is also very regular, very complex, it must have been difficult to put together, therefore, if one has a designer, the other has a designer. What else might you ask? Okay, there is a similarity, we might say, between pocket watches and the universe.we might say between pocket watches and the universe, but there are many, many dissimilarities. Why should we consider that this similarity is more important than all these differences? Yep. OK. But wouldn’t you say that if the universe is like a pocket watch in this particular thing and the explanation of pocket watches having a designer is this particular thing, In other words, it’s being very complex. So if we agree that everything that’s complex and regular must have a designer.

[译文 30]

好的，我们该怎样来质疑这个论证呢？是的，好，我们这里挑出的是哪个方面，并说它与那两个例子相似呢？所以为什么宇宙像一块怀表呢？我的意思是，用这个著名的例子，那个人相信什么？那是极其错综复杂的。那就是那个人会说的。没错，那是非常……那是谁来着？完全想不起来了……佩里。没错，谢谢你。对不起，我脑子里一团糟，非常奇怪。是的，佩里相信怀表是规律运行的，它非常复杂，把它组装起来一定非常困难，而他相信宇宙也是非常有规律、非常复杂的，把它组装起来一定很困难，因此，如果一个有设计者，另一个也有设计者。你还会问什么？好的，我们可以说，怀表和宇宙之间有一种相似性，我们可以说怀表和宇宙之间，但也有许许多多的不同之处。我们凭什么认为这种相似性比所有这些差异更重要呢？是的。好。但你难道不认为吗，如果宇宙在这一点上像怀表，而怀表有设计者的解释就是这一点——也就是说，它是非常复杂的。那么如果我们同意所有复杂而规律的事物都必须有设计者。

[段 31]

OK, but we are saying the universe is like a pocket watch in being very complex and regular. Pocket watches have a designer. Oh, I see. OK, so you’re absolutely right. I’m sorry, no, you are right. I was changing that second premise to everything that’s complicated has a designer. And that’s not what it says, is it? And so I’ve rightly been pulled up on that. OK, it isn’t what it says. I suppose that’s why we think that this is going to work at all, though, isn’t it? In order to give an argument, we do have to say a lot of things in support of the various premises and in support of our belief that the conclusion follows from the premise and so on. So you wouldn’t expect almost anything said to be an argument. And actually, as you learn… Yes, no, I’m not surprised that…Yes, no, I’m not surprised. I suppose what I’m doing is I’m defending newspapers because actually you need to read a whole article in order to see what the claim being made is. And then you need to go back and identify what the reasons are being given for the claim. OK, are the two things similar in the respect of, is the respect in which they’re similar relevant to the argument being made? And also, can we find a disanalogy, which is the thing you mentioned is, are there differences between them and do the differences pertain to this argument?

[译文 31]

好，但我们要说的是，宇宙在非常复杂和规律这一点上像怀表。怀表有设计者。哦，我明白了。好，所以你是完全正确的。对不起，不，你是对的。我把第二个前提改成了所有复杂的事物都有设计者。而那不是它所说的，对吧？所以我被纠正得没错。好，它说的不是这个。我想这就是为什么我们认为这整件事行得通的原因，不是吗？为了给出一个论证，我们确实必须说很多东西来支持各个前提，并支持我们相信结论是从前提中推出的，诸如此类。所以你不会期望几乎任何说出来的东西都是一个论证。事实上，随着你学习的深入……是的，不，我并不感到惊讶……是的，不，我并不感到惊讶。我想我这样做是在为报纸辩护，因为实际上你需要读完一整篇文章才能看出其中的主张是什么。然后你需要回过头来去识别为这个主张给出的理由是什么。好，这两件事在某一方面相似吗，这种相似的方面与正在进行的论证相关吗？而且，我们能否找到一个差异，也就是你提到的事情，它们之间是否存在差异，而这些差异是否与这个论证有关？

[段 32]

But the thing to remember about arguments from analogy is that they are extrapolating from just one example. Therefore, the one example and the extrapolation have to be really pretty strong before you should go along with them. So, arguments from analogy are much more common and probably for the reason you’re saying, because they often take us along with them emotionally. Let’s finally look at arguments from authority, which take one person or a group of persons who are or are assumed to be right about some things and they extrapolate to the claim that they’re right about other things. So human rights monitoring organisations are experts on whether human rights have been violated. They say that some prisoners are mistreated and extraditedthey say that some prisoners are mistreated in Mexico therefore some prisoners are mistreated in Mexico what do we need to ask about this? What’s the source of their information? Where do they get their information from? Is it just that they’ve become hackneyed and cynical and they think that everyone mistreats everyone or do they actually have reasons for saying what they have? Yep. I mean all that’s needed for this argument is that some prisoners are mistreated not that they’re mistreated by anyone in particular, I think. Okay, you might say here, we’ve started the first premise here, is they may be experts on whether human rights have been violated, but are they experts on whether somebody’s been mistreated?

[译文 32]

但要记住的一点是，关于类比论证，它们只是从一个例子进行外推。因此，这一个例子以及这种外推必须真的相当有力，你才应该赞同它们。所以，类比论证要常见得多，可能就是因为你所说的那个原因，因为它们经常在情感上带着我们走。最后让我们来看看权威论证，它取一个或一组被假定在某些事情上正确的人，然后外推出他们在其他事情上也正确。所以人权监督组织是判断人权是否受到侵犯的专家。他们说一些囚犯在墨西哥受到虐待并被引渡——他们说一些囚犯在墨西哥受到虐待，因此一些囚犯在墨西哥受到虐待——我们需要问什么呢？他们的信息来源是什么？他们从哪里获得信息？是因为他们变得陈腐和愤世嫉俗，认为每个人都在虐待每个人，还是他们实际上有理由说他们所说的那些话？是的。我的意思是，这个论证所需要的只是一些囚犯受到虐待，而不是他们被某个特定的人虐待，我想。好的，你可能在这里说，我们从第一个前提开始，他们可能是关于人权是否受到侵犯的专家，但他们是关于某人是否受到虐待的专家吗？

[段 33]

Are they perhaps seeing trivial forms of mistreatment as violations of human rights or something? Is that what you mean? Yeah, okay. Okay, well, let’s have a look at the… Okay, who exactly is the source of information? I mean, it was saying there, it was implying at least that all the human rights organisations were saying it, but it might just say one. And again, there you would want to make a judgment about whether the source of information really is an expert, whether they’re qualified in the appropriate area, because it’s very easy, again, going back to how inductively bold you are, If you have a tendency to think this person is an expert in one area, you may well inductively generalize to his or her being an expert in another area. So your tutor, for example, whom you think is, you know, if Marianne says P, then P, which is, of course, a very good argument.

[译文 33]

他们是不是可能把轻微形式的虐待视为对人权的侵犯或类似的情况？你的意思是这个吗？是的，好。好的，好，我们来看看……好的，信息的来源究竟是谁？我的意思是，那里说的，它至少在暗示所有的人权组织都在这样说，但也可能只是一个。而且再次，在那里你要对信息源是否真的是专家做出判断，他们在合适的领域是否有资格，因为再一次，回到你在归纳上有多大胆这个问题上，如果你倾向于认为这个人在一个领域是专家，你很可能会归纳地推广到认为他或她在另一个领域也是专家。所以比如说你的导师，你认为，你知道，如果玛丽安说 P，那么 P 就是 P，这当然是一个非常好的论证。

[段 34]

But if what she’s talking about is politics or mathematics or something like that, then it’s complete nonsense, isn’t it? okay so not only that you need to know who they are you need to know whether they’re qualified in the right area you need to know whether they’re impartial in this in respect to this particular claim so Amnesty International let’s say are impartial they go out and they get the evidence and they’re very careful not to be biased I don’t know whether that’s true incidentally but let’s say it could be but then there might be another human rights organization that’s not careful to make sure that its information isn’t biased so you’d need to make a distinction between the fact that amnesty is a reputable organization and this other one isn’t well I mean you get that quite often I mean I mean if you want to belittle the results that have come out of a particular survey one way of doing it is to say that the people who are who are putting forward this survey are biased so for I’ve been working on looking at GM food and actually it’s very very difficult to to get a source that hasn’t been funded by a pharmaceutical company or by a company that isn’t the soil association or somebody that’s very anti-GM foods. So finding something that really is an impartial source is really very difficult.

[译文 34]

但如果她谈论的是政治或数学或类似的东西，那就完全是胡说八道了，不是吗？好的，所以不仅需要知道他们是谁，还需要知道他们在正确的领域是否有资格，还需要知道他们就这个特定主张而言是否公正。所以比如说国际特赦组织，他们是公正的，他们出去收集证据，并且非常小心地避免偏见，我顺便不知道这是否是真的，但假设可能是这样。但可能还有另一个人权组织不那么小心地确保其信息没有偏见。所以你需要区分这样一个事实：国际特赦是一个有声誉的组织，而这个其他的不是。嗯，我的意思是这种情况经常发生，我的意思是我的意思是如果你想贬低某项特定调查所产生的结果，一种方法就是说提出这项调查的人是有偏见的。所以我一直在研究转基因食品，实际上非常非常难以找到一个没有被制药公司资助的信息来源，或者没有被土壤协会或某个非常反对转基因食品的组织资助的信息来源。所以要找到一个真正公正的信息源真的非常困难。

[段 35]

And it’s very, very important to try and find one if you’re really going to evaluate these arguments. finally the point you made a minute ago it’s very rarely the case that you have one expert in an area and it’s very rarely the case also that all the experts in an area will agree on something and if you have different experts making different claims you need to make a judgment as to where you think which of them you think is correct and what you can’t rely on there is an argument from authority can you? Because they’re both authorities. So if you were an undergraduate writing an essay, or indeed if you were you writing an essay on philosophy, for me, I would have given you lots of reading, you would have done the reading, and I would have expected you to come away and to think, okay, well, so-and-so says this, and thingamabob says that, and he says P and he says not P, well which of them is the case? Well now you need to look at what the arguments are that so and so gives, what the arguments are that thingamabob gives and work out which ones you think are the best onesand work out which ones you think are the best ones and why. So there’s no substitute for thinking for yourself. An appeal to an argument for authority is okay for various things.

[译文 35]

而且如果你真的要评估这些论证的话，努力找到一个这样的信息源是非常非常重要的。最后，你刚才提到的那一点，在某个领域你有一个专家的情况非常少见，而且在一个领域中所有专家在某一件事上意见一致的情况也非常少见。如果你有不同专家做出不同的主张，你需要对他们中你认为正确的那个做出判断，而在这一点上你不能依赖的是一个权威论证，对吧？因为他们都是权威。所以如果你是本科生在写一篇论文，或者实际上如果你是在写一篇关于哲学的论文，对我来说，我会给你大量的阅读材料，你会完成这些阅读，而我会期望你看完之后去思考，好的，那么某某人是这样说的，而 thingamabob 是那样说的，他说 P 而他说非 P，那么哪种情况成立呢？那么现在你需要看看某某人所给出的论证是什么，thingamabob 所给出的论证是什么，并弄清楚你认为哪些是最好的，弄清楚你认为哪些是最好的以及为什么。所以没有什么可以替代你自己的思考。诉诸权威论证对于各种事情来说是可以的。

[段 36]

I mean, we have to rely on authorities for all sorts of things. But if you were trying to write a philosophy essay saying Marianne says P, therefore P, will not do. and that’s true of every philosopher you ever come across because there are very, very few things in philosophy that aren’t questioned. Okay, that’s where I was going today. Next week we’ll look at validity and truth and then we’ll turn to the evaluation of deductive arguments.

[译文 36]

我的意思是，我们在各种事情上都必须依赖权威。但如果你要写一篇哲学论文说"Marianne 说 P，所以 P"，那是行不通的。这一点对你所遇到的每一位哲学家都适用，因为哲学中很少有不被质疑的东西。好的，今天就讲到这里。下周我们将讨论有效性和真值，然后转向对演绎论证的评估。