WEBVTT 00:01.550 --> 00:03.770 Prof: This is data from Bolivia. 00:03.770 --> 00:07.830 It came out the end of last year and it's from the year 00:07.833 --> 00:08.363 2003. 00:08.360 --> 00:10.880 Demographic data is always delayed because it takes a long 00:10.877 --> 00:12.377 time to collect it, and analyze it, 00:12.379 --> 00:13.129 and so forth. 00:13.130 --> 00:19.530 This is a fairly standard thing that's happening. 00:19.530 --> 00:23.040 This is various five year bunches, they take these surveys 00:23.038 --> 00:25.938 every five years, this is from a thing called The 00:25.940 --> 00:29.010 Demographic and Health Surveys which are done basically in 00:29.012 --> 00:32.302 every developing country of the world by their own statistical 00:32.299 --> 00:32.999 service. 00:33.000 --> 00:36.570 Every country has a fairly decent census and statistical 00:36.567 --> 00:39.937 service and they go and ask either all the women, 00:39.940 --> 00:42.990 if it's a census year, or a subset of the women if 00:42.994 --> 00:46.864 it's not a census year and they ask all kinds of questions, 00:46.860 --> 00:49.370 some of which you will see. 00:49.370 --> 00:53.010 The first thing of course is how many children do you have? 00:53.010 --> 00:55.760 They used--when they started these kind of surveys they used 00:55.761 --> 00:58.281 to ask men and they would get a number, the husband. 00:58.280 --> 01:01.010 Then they'd ask the wife, get a different number, 01:01.011 --> 01:04.481 and when they checked it turns out the woman was right and the 01:04.481 --> 01:05.621 man had no clue. 01:05.620 --> 01:09.670 Veena will tell you, maybe some stories about it's 01:09.665 --> 01:14.035 not even a simple question, even to the woman how many 01:14.042 --> 01:16.192 children have you had. 01:16.188 --> 01:19.348 In a lot of ways, men's data was unreliable and 01:19.348 --> 01:23.258 in the early days they really were interested in getting a 01:23.262 --> 01:25.202 real ground-- they didn't know how many 01:25.197 --> 01:27.417 people there were in the world, what the fertility rates were, 01:27.424 --> 01:28.804 how fast population was growing, 01:28.799 --> 01:33.969 so just to get the basic ideas, women were asked. 01:33.970 --> 01:36.870 From that date on men have somewhat been excluded from the 01:36.872 --> 01:39.212 data collection, so a lot of what we know, 01:39.209 --> 01:42.059 in fact almost all of what we know is about women, 01:42.060 --> 01:43.480 but nowadays its changing. 01:43.480 --> 01:47.250 In the last number of year's people realize it takes two to 01:47.251 --> 01:51.091 tango and men are starting to come more into the picture. 01:51.090 --> 01:54.730 Anyway here by 19--so this is a five-year age group and this is 01:54.733 --> 01:56.323 the total fertility rate. 01:56.319 --> 02:01.029 In 1965 and 1970 and other years they were having roughly 02:01.025 --> 02:05.215 6.6 children, then gradually every five-year 02:05.221 --> 02:10.641 increment it came down until the most recent number is 3.8 02:10.639 --> 02:11.779 children. 02:11.780 --> 02:15.870 Now keep that 3.8 number in mind because we want to compare 02:15.870 --> 02:19.820 that to some other things, and you probably know a little 02:19.819 --> 02:21.089 about Bolivia. 02:21.090 --> 02:24.500 It's totally Catholic, it's quite poor, 02:24.500 --> 02:28.610 it's mostly agricultural, it's not very urbanized, 02:28.610 --> 02:30.950 education is at a fairly low level, 02:30.949 --> 02:33.979 and the status of women there is not really wonderful. 02:33.979 --> 02:38.269 With all those indicate--what they call social indicators what 02:38.269 --> 02:42.069 would you think about the fertility desires of women in 02:42.066 --> 02:42.906 Bolivia? 02:42.910 --> 02:46.890 High? Low? 02:46.889 --> 02:47.159 High. 02:47.160 --> 02:50.230 All of those are sort of standard classical factors that 02:50.234 --> 02:53.424 would make you think that they want a lot of children, 02:53.419 --> 02:57.379 but when you look at the actual data it's rather moderate. 02:57.378 --> 03:01.978 It's still very high by our standards of one or two children 03:01.977 --> 03:05.177 but still-- and it's still important for 03:05.175 --> 03:09.545 the world because at 3.8 you double the population almost 03:09.549 --> 03:11.459 every-- not quite double it every 03:11.462 --> 03:13.052 generation so this is quite high, 03:13.050 --> 03:17.370 but it's nothing like a 6,7 child thing or in the past the 03:17.366 --> 03:23.676 traditional number of 7 or 8, or maybe 9 children per woman, 03:23.681 --> 03:29.261 so it's a situation of moderate fertility. 03:29.258 --> 03:32.828 Now what--the next kind of set of questions is well this is the 03:32.834 --> 03:36.124 number of children you're having, how many do you want? 03:36.120 --> 03:40.000 They asked--this is asked--it's a very tricky kind of question 03:39.997 --> 03:43.617 as you'll probably hear so there's a lot of different ways 03:43.622 --> 03:45.532 of spinning this question. 03:45.530 --> 03:52.450 The first is they ask you, 'did you want your last child?' 03:52.449 --> 03:58.029 That has a whole complicated set of answers and just look out 03:58.032 --> 04:03.712 here for the total numbers that 'did you want the child at the 04:03.710 --> 04:06.130 time that you had it?' 04:06.128 --> 04:11.558 Well 38% of women said, yes I wanted it when I had it, 04:11.556 --> 04:16.676 but not wanted at all, somewhat larger 40% of women 04:16.677 --> 04:19.337 didn't want it at all. 04:19.339 --> 04:23.499 That's a surprising split and then in between there's another 04:23.495 --> 04:26.885 20% of women who gave a more ambiguous answer, 04:26.889 --> 04:30.599 'well I didn't really want the child right then but I probably 04:30.596 --> 04:34.486 would have wanted a child in the future,' and a lot of guess work 04:34.485 --> 04:38.125 on the part of the respondent in that about what their future 04:38.132 --> 04:39.472 desires will be. 04:39.470 --> 04:41.990 As you know, humans change their mind every 04:41.990 --> 04:44.150 five minutes on important topics, 04:44.149 --> 04:49.509 but that's a very interesting statistic that there's more 04:49.505 --> 04:54.855 children unwanted than are wanted and that's somewhere in 04:54.862 --> 04:56.012 between. 04:56.009 --> 04:58.609 Now there's probably a lot of bias in this data. 04:58.610 --> 05:01.190 This is not considered wonderful data because you're 05:01.194 --> 05:04.344 asking a woman who's just had a child, or fairly recently had a 05:04.336 --> 05:06.106 child, did you want that child? 05:06.110 --> 05:09.680 What's the bias? 05:09.680 --> 05:11.390 You say yes. 05:11.389 --> 05:14.679 I mean it's very--you have to really not like that child in 05:14.680 --> 05:17.180 order to say, 'oh yeah I had him but I didn't 05:17.175 --> 05:17.965 want him.' 05:17.970 --> 05:23.020 It happens and you see that at 40% of women do say that, 05:23.019 --> 05:27.849 but this data is probably biased to put more kids in this 05:27.853 --> 05:31.743 category then what the woman really feels, 05:31.740 --> 05:35.920 although again, intentions are very changeable 05:35.916 --> 05:39.346 and attitudes toward other people, 05:39.350 --> 05:41.850 husbands, children, one minute you love them and 05:41.853 --> 05:44.093 the next minute hate them and so forth, 05:44.089 --> 05:49.739 so that's problematic, the data there. 05:49.740 --> 05:53.600 One way of getting around that particular problem is to ask 05:53.596 --> 05:56.246 them, 'do you want another child in 05:56.250 --> 05:59.540 the future' because that's more volitional, 05:59.540 --> 06:02.800 that's not saying I did something wrong or something 06:02.802 --> 06:06.132 that I didn't want and so here's that set of data; 06:06.129 --> 06:10.119 again all this from the Demographic and Health Survey. 06:10.120 --> 06:12.190 Again it's sort of what you would expect, 06:12.185 --> 06:15.015 this is women who don't want, want to stop childbearing, 06:15.024 --> 06:16.734 don't want any more children. 06:16.730 --> 06:22.740 If they've had no children already very few of them don't 06:22.737 --> 06:25.417 want any children 6.5%. 06:25.420 --> 06:29.190 If they've had one child already 30% say one child is 06:29.189 --> 06:31.219 enough, I'm ready to stop. 06:31.220 --> 06:35.810 If they had two children you're up to 2/3 of the women now say 06:35.812 --> 06:39.582 that's enough for me, I want to stop and when you get 06:39.584 --> 06:42.124 to three you're almost at the maximum, 06:42.120 --> 06:48.610 and then four and above you're into the 91%-92%. 06:48.610 --> 06:51.750 You notice it's kind of interesting that it rises and 06:51.750 --> 06:55.280 then it stays flat, so there's about 8% of women 06:55.279 --> 07:00.149 who no matter how many children they have they always say 'no I 07:00.149 --> 07:02.219 want more, I don't want to stop.' 07:02.220 --> 07:05.960 This is what we call very traditional women, 07:05.959 --> 07:11.459 that as many as God gives me, here comes in one version or 07:11.458 --> 07:13.988 another, but it's 8% it's a very small 07:13.992 --> 07:16.692 number, women who don't seem to have an 07:16.685 --> 07:20.215 idea of some number at which they want to stop, 07:20.220 --> 07:24.060 or some of them they've already had whether they want to now 07:24.055 --> 07:24.505 stop. 07:24.509 --> 07:28.739 07:28.740 --> 07:36.690 Now you can ask another kind of question, 07:36.690 --> 07:40.530 you say this is called an ideal number of children, 07:40.529 --> 07:43.169 and you ask a question like, if you could go back to the 07:43.170 --> 07:45.140 beginning before you had any children, 07:45.139 --> 07:50.059 how many children would you have wanted as your ideal 07:50.057 --> 07:50.907 number? 07:50.910 --> 07:55.770 You get these kinds of numbers that women who have no children 07:55.767 --> 08:00.387 want to have two--who now have no children asking what they 08:00.387 --> 08:04.567 think their ideal was; they want 2.1 children. 08:04.569 --> 08:09.759 Women who already have one child 2.1, those that have two 08:09.755 --> 08:15.215 say 2.4, and then the number goes on up, including women who 08:15.221 --> 08:18.001 have six or more children. 08:18.000 --> 08:23.680 Now it's pretty clear that one should really expect this kind 08:23.682 --> 08:28.202 of thing because the simplest, most obvious reason is, 08:28.202 --> 08:31.172 women who want more children have more children. 08:31.170 --> 08:33.860 As you have more children that's a sign that you wanted 08:33.861 --> 08:34.661 more children. 08:34.658 --> 08:36.918 That certainly may be the biggest factor, 08:36.921 --> 08:38.901 just a very simple kind of thing. 08:38.899 --> 08:42.969 Another factor is women who have had more children are 08:42.974 --> 08:43.594 older. 08:43.590 --> 08:46.650 Remember we're talking about a period in history, 08:46.649 --> 08:49.659 I mean this is recent, where ideas are changing, 08:49.658 --> 08:52.058 fertility is changing, standards and norms and 08:52.058 --> 08:56.408 personal desires are changing, so the older women just by the 08:56.408 --> 09:01.588 age factor will probably be of a somewhat older generation. 09:01.590 --> 09:04.970 I won't go into it but this looks at that, 09:04.970 --> 09:07.400 here is the age of a woman and again, 09:07.399 --> 09:09.169 how many if you went back to the beginning, 09:09.168 --> 09:13.148 how many children would you have liked and you get just an 09:13.150 --> 09:15.550 age factor, but not wildly different from 09:15.546 --> 09:15.836 this. 09:15.840 --> 09:21.790 Just generational change is a bigger factor in that then you 09:21.794 --> 09:23.314 might expect. 09:23.308 --> 09:26.988 And also in this rise is what we've just talked about that 09:26.985 --> 09:29.625 women already had a bunch of children, 09:29.629 --> 09:33.419 when they reconstruct back what they used to think or now think 09:33.423 --> 09:36.673 that they would think they-- again well I have three I'm 09:36.672 --> 09:39.132 either happy or whatever they think about it, 09:39.129 --> 09:44.689 it's hard for them to say no I don't want this many. 09:44.690 --> 09:47.740 Have you noticed anything funny now? 09:47.740 --> 09:53.470 Anything about the number, these numbers and the number I 09:53.466 --> 09:55.816 told you to remember? 09:55.820 --> 09:58.960 No class of woman wants more than 3.3 children. 09:58.960 --> 10:02.810 Most of the women are in the two range and only those that 10:02.812 --> 10:05.452 have six and more children want 3.3, 10:05.450 --> 10:07.980 and the same if you look it out by age, 10:07.980 --> 10:10.990 no group of women wants more than three. 10:10.990 --> 10:13.300 What did I say about how many they're having? 10:13.299 --> 10:15.779 3.8. 10:15.778 --> 10:19.698 This now accords with the other stuff that you've seen that 10:19.702 --> 10:23.972 women want--it looks like women want fewer children than they're 10:23.965 --> 10:24.705 having. 10:24.710 --> 10:28.910 Well this is Bolivia, maybe there's something a 10:28.910 --> 10:32.200 little bit special about Bolivia, 10:32.200 --> 10:35.370 and you always have to check and see whether you're getting 10:35.369 --> 10:38.429 some sort of outlier or is this the general situation. 10:38.428 --> 10:44.708 You don't have to look at that too closely yet. 10:44.710 --> 10:48.450 An economist at The World Bank, a guy named Lant Pritchett, 10:48.447 --> 10:52.507 did a paper and the first thing he did was collect all that data 10:52.506 --> 10:53.986 from every country. 10:53.990 --> 10:58.300 These Demographic and Health Surveys are published every time 10:58.302 --> 11:02.402 a country does its own statistical demographic survey, 11:02.399 --> 11:04.689 and so all of this information is available, 11:04.690 --> 11:07.260 and now it's computerized and so forth, 11:07.259 --> 11:09.349 and there's uniformity. 11:09.350 --> 11:14.090 There's a group called Macro International that sort of helps 11:14.091 --> 11:18.831 these various countries design these surveys so that they can 11:18.833 --> 11:23.813 be compared internationally and get fairly good comparability of 11:23.813 --> 11:25.003 the data. 11:25.000 --> 11:27.750 What he did is, of these various statistical 11:27.746 --> 11:31.326 ways of finding out how many children women want and they 11:31.325 --> 11:33.045 have different numbers. 11:33.048 --> 11:35.218 This is average ideal number of children, 11:35.220 --> 11:40.450 this is desired total fertility rate, 11:40.450 --> 11:43.440 and here's a third one, the wanted total fertility rate 11:43.442 --> 11:46.432 and they all correct for different factors in different 11:46.434 --> 11:49.214 ways, but the only thing I think that 11:49.211 --> 11:53.731 you have to sort of notice is that they're all about the same. 11:53.730 --> 11:59.310 No matter how you spin this you get a picture that looks 11:59.307 --> 12:01.537 something like this. 12:01.539 --> 12:03.089 What is it? 12:03.090 --> 12:07.020 Wanted TFR, in this case is how many children does the woman 12:07.023 --> 12:07.493 want? 12:07.490 --> 12:09.720 Self report, this is how many she says she 12:09.716 --> 12:12.426 wants, do you want 2,3, 4,5, 6,7, 8 and this is the 12:12.432 --> 12:13.792 total fertility rate. 12:13.788 --> 12:17.028 How many children is she actually having? 12:17.028 --> 12:22.378 The countries are luckily all named here, and you can see 12:22.375 --> 12:26.955 Syria for instance, the women want 5 children and 12:26.956 --> 12:28.576 they're having 7. 12:28.578 --> 12:30.868 something children. 12:30.870 --> 12:37.700 Here is--pick another one, Pakistan, they want 4 children 12:37.702 --> 12:41.122 they're having 6 children. 12:41.120 --> 12:46.040 You can look at that and every country is in there. 12:46.038 --> 12:51.238 One important thing is how important the desire, 12:51.240 --> 12:53.930 whatever children want, that there's a very strong 12:53.931 --> 12:57.171 correlation between the number of children that you want and 12:57.172 --> 12:59.702 the number of children you actually have, 12:59.700 --> 13:00.940 aggregated by country. 13:00.940 --> 13:03.760 I mean we're taking a lot of people and lumping them into two 13:03.761 --> 13:05.811 numbers, this number and this number, 13:05.813 --> 13:09.053 and there's great variation of course within in each country 13:09.048 --> 13:11.458 but that's certainly an important factor. 13:11.460 --> 13:13.760 The key line, because Pritchett in gathering 13:13.761 --> 13:16.871 this data, wanted to make a different point which we're not 13:16.866 --> 13:18.256 going to get to today. 13:18.259 --> 13:22.689 He leaves out a really important line here which is 13:22.690 --> 13:25.880 this line that I've drawn this in. 13:25.879 --> 13:26.999 What line is that? 13:27.000 --> 13:30.250 That's the line where it is if you want two children you have 13:30.251 --> 13:32.871 two children, if you want three children you 13:32.868 --> 13:35.918 have three children, if you want nine children you 13:35.923 --> 13:39.193 have nine children, so any country that was on that 13:39.190 --> 13:42.640 line people are having the number of children that they 13:42.639 --> 13:43.149 want. 13:43.149 --> 13:46.009 What do you notice about all these countries? 13:46.009 --> 13:49.439 Every single one of them is above the line, 13:49.440 --> 13:53.930 meaning that in every single country they're having more 13:53.932 --> 13:56.222 children then they want. 13:56.220 --> 13:57.890 What they want is what they have; 13:57.889 --> 14:00.889 they're all above that line of equality. 14:00.889 --> 14:04.319 This is some of the cleanest social science data I have ever 14:04.323 --> 14:06.803 seen, the way they're all one side of 14:06.803 --> 14:09.503 the line, they follow very nicely the 14:09.501 --> 14:10.751 regression line. 14:10.750 --> 14:15.020 This is the regression line that he drew in which is just a 14:15.017 --> 14:18.767 line that is closest to all the points together, 14:18.769 --> 14:26.779 a statistical way of making the line as close as possible to all 14:26.783 --> 14:28.823 of the points. 14:28.820 --> 14:34.430 This gap here between what people want, if they got what 14:34.427 --> 14:40.437 they wanted and what they're actually having is called unmet 14:40.442 --> 14:41.362 need. 14:41.360 --> 14:44.260 A very complicated idea, much argued about, 14:44.259 --> 14:46.959 and Veena may or may not discuss it, 14:46.960 --> 14:51.950 but what it tells you is that there's a very noticeable 14:51.947 --> 14:55.507 difference between-- it's describing that difference 14:55.509 --> 14:58.619 between the number of children people have and what they want. 14:58.620 --> 15:04.800 It's roughly one child per family here. 15:04.798 --> 15:08.528 This number in principle should be one and a half children, 15:08.530 --> 15:11.810 but there's certain connections, it's actually about 15:11.811 --> 15:15.421 one child per family; the difference between what 15:15.423 --> 15:17.653 they have and what they want. 15:17.649 --> 15:23.279 Now in the developing world this is a little bit old data, 15:23.280 --> 15:29.110 but in the developing world today the average fertility rate 15:29.110 --> 15:30.790 is about 3.5. 15:30.788 --> 15:34.458 In order to come to stable population in the developing 15:34.456 --> 15:36.896 world it has to come down to 2.1, 15:36.899 --> 15:39.519 but if all the women here in these countries that are 15:39.519 --> 15:43.189 reporting what they want, if they actually had the number 15:43.186 --> 15:47.696 of children that they want you'd subtract out from the 3.5 (one 15:47.698 --> 15:51.098 child), you're down to 2.5 and you're 15:51.095 --> 15:56.275 actually very close then to what's called replacement level 15:56.284 --> 15:59.064 fertility this 2.1 children. 15:59.058 --> 16:04.848 This difference of what women want and what they have is an 16:04.852 --> 16:07.652 extremely important issue. 16:07.649 --> 16:12.579 In one version of the kind of thing that Planned Parenthood 16:12.576 --> 16:17.246 and other international and domestic organizations do is 16:17.248 --> 16:21.578 help women get to the fertility that they want. 16:21.580 --> 16:26.150 Not as pushing them into something but giving them 16:26.153 --> 16:29.423 something that they already want. 16:29.418 --> 16:32.518 This data, as in all data, brings up a whole bunch of 16:32.523 --> 16:33.243 questions. 16:33.240 --> 16:35.920 One: does this really reflect people's data? 16:35.918 --> 16:38.808 Have we actually--have these kinds of questions and this kind 16:38.807 --> 16:41.647 of statistical analysis really tapped into the real emotions 16:41.647 --> 16:43.137 and feelings of the people? 16:43.139 --> 16:46.809 You always have to question these kinds of survey data. 16:46.808 --> 16:52.368 You remember that you read this in readings in Africa, 16:52.370 --> 16:55.340 that when the women were asked how many children do you want, 16:55.340 --> 16:56.860 it was a meaningless question to them. 16:56.860 --> 16:59.320 They said whatever Ala says, whatever God says, 16:59.323 --> 17:02.543 they can't--it's just not in their--what their technical term 17:02.538 --> 17:04.518 is 'calculus of rational choice.' 17:04.519 --> 17:10.029 Well there's women like that in this survey and what number do 17:10.030 --> 17:12.200 you put down for them? 17:12.200 --> 17:14.680 These women, as I've said is basically--is 17:14.683 --> 17:16.323 all collected from women. 17:16.318 --> 17:18.338 What about men, do men want more children? 17:18.339 --> 17:19.199 Do they want the same? 17:19.200 --> 17:20.480 Do they want less? 17:20.480 --> 17:22.620 Is it that women's desires don't matter? 17:22.618 --> 17:27.128 It is men's desires that really matter? 17:27.130 --> 17:31.770 Why do women up here in Kenya and Mali at this time want so 17:31.769 --> 17:35.129 many children and have so many children? 17:35.130 --> 17:38.730 Whereas, countries you might not think of wildly different 17:38.728 --> 17:42.448 Trinidad, Dominican Republic, Fiji, various other places are 17:42.452 --> 17:43.592 way down here. 17:43.588 --> 17:50.518 Why some countries here and some countries there? 17:50.519 --> 17:54.499 Another thing is that in most of the world people actually 17:54.496 --> 17:56.376 know about contraception. 17:56.380 --> 18:02.450 Here is data again from the Bolivian survey 2003 and do they 18:02.452 --> 18:05.852 know a method of contraception? 18:05.848 --> 18:10.158 Well they know any method yeah, 95% of the women know about 18:10.164 --> 18:12.994 contraception, and even the modern methods 18:12.986 --> 18:15.966 which are listed here, 92% of the women they know 18:15.970 --> 18:19.970 about it and many of the women know about more than one method, 18:19.970 --> 18:23.620 so 80% know about the pill, another 80% the IUD, 18:23.619 --> 18:25.019 another 80% the injectables. 18:25.019 --> 18:27.199 That means there's a lot of overlap between these. 18:27.200 --> 18:29.420 They don't know one method, they know two, 18:29.417 --> 18:32.827 and three, and male condom they know about, female sterilization 18:32.826 --> 18:34.446 they know about and so on. 18:34.450 --> 18:39.170 This is lactational amenorrhea which is the traditional method 18:39.173 --> 18:43.283 that we've talked about of spacing births and half the 18:43.279 --> 18:47.229 women know that if you breastfeed you'll prolong the 18:47.229 --> 18:49.939 interval between your births. 18:49.940 --> 18:53.570 Not only do they know about the method but they've used the 18:53.565 --> 18:56.215 method, 77% of women have tried 18:56.218 --> 19:01.768 something, a fair amount of that is 20% of these women are using 19:01.773 --> 19:07.333 only traditional methods which include rhythm type methods, 19:07.328 --> 19:13.048 but still 57% have actually used a modern method. 19:13.049 --> 19:17.209 Currently using drops down. 19:17.210 --> 19:20.630 They've tried it and for some reason they've stopped. 19:20.630 --> 19:34.350 19:34.348 --> 19:39.048 One is this medical problem that the dominant reason why 19:39.047 --> 19:42.887 women say they're not using contraception-- 19:42.890 --> 19:45.510 so you've seen the data, they want to stop childbearing, 19:45.509 --> 19:46.569 it's overwhelming. 19:46.568 --> 19:49.328 You saw like Bolivia--what was the final number, 19:49.328 --> 19:59.098 I don't know I pointed it out, 70% I think it was-- 19:59.098 --> 20:01.908 something like 70% of the women say ‘I don't want any more 20:01.911 --> 20:04.311 children ever, I want to just plain old stop,' 20:04.308 --> 20:07.218 and then if you add in those that are not sure about the 20:07.218 --> 20:09.198 future, but they say well at least not 20:09.202 --> 20:12.112 in the next two years and then beyond two years I don't know so 20:12.105 --> 20:15.185 you add at least another 10%-- something like 80% of women 20:15.190 --> 20:19.390 want some kind of protection, they either want to mostly stop 20:19.390 --> 20:22.840 totally or at least for the next two years. 20:22.838 --> 20:25.818 You can even go down, this is again older data from 20:25.824 --> 20:28.454 Bolivia, that's one of my favorite places; 20:28.450 --> 20:32.310 I was--spent some good times there. 20:32.308 --> 20:36.938 If you just take teenagers age 15 to 19 already about 40% of 20:36.943 --> 20:41.273 them say I've had all the children I want the whole rest 20:41.265 --> 20:46.445 of my life and the average age of that sample is 17 years old. 20:46.450 --> 20:50.260 So you have these huge number of women who don't want-- 20:50.259 --> 20:53.659 want to stop childbearing and yet if you look from the 20:53.657 --> 20:57.887 Demographic and Health Surveys at the contraceptive prevalence, 20:57.890 --> 21:00.740 like in Bolivia again, at the time of Robey article 21:00.744 --> 21:03.834 that you have read last night or are going to read, 21:03.828 --> 21:06.798 the women who want protection either-- 21:06.798 --> 21:10.428 are about--were about 80% and the women that were using 21:10.425 --> 21:15.275 protection was like 12%, and you ask them why and 21:15.280 --> 21:20.350 largely, and especially more recently, 21:20.349 --> 21:22.819 it's medical reasons. 21:22.818 --> 21:25.478 There is first of all a campaign by conservative, 21:25.480 --> 21:29.810 especially religious people in places like Kenya to-- 21:29.808 --> 21:33.378 they're opposed to the use of contraception and they really 21:33.384 --> 21:36.844 blow up medical problems, so the people are getting very 21:36.843 --> 21:38.233 poor information on it. 21:38.230 --> 21:41.700 Now here's an example, one of the undergraduates that 21:41.700 --> 21:44.170 took this course a few years back, 21:44.170 --> 21:48.630 a very energetic young lady and she got interested in this stuff 21:48.625 --> 21:53.005 and so I arranged for her to go to Kenya to answer exactly this 21:53.009 --> 21:53.929 question. 21:53.930 --> 21:57.830 Why is it that women--and you'll hear a little later-- 21:57.828 --> 22:01.698 why is it that women who say they don't want any children, 22:01.700 --> 22:05.210 they're living in Nairobi and there's plenty of contraceptives 22:05.207 --> 22:08.827 available in Nairobi and you can get them more or less free, 22:08.828 --> 22:12.928 or a small cost, and they're not using it, 22:12.930 --> 22:15.300 then they get pregnant. 22:15.298 --> 22:17.278 They can't have that baby, they don't want the baby, 22:17.278 --> 22:20.248 so they go to some bush doctor, and it's illegal in most of 22:20.248 --> 22:21.808 Africa, Sub-Saharan Africa, 22:21.808 --> 22:24.128 all of Africa, abortion is illegal but here 22:24.127 --> 22:27.217 they got pregnant so they go to some horrible clinic. 22:27.220 --> 22:29.340 The death rate is very, very high. 22:29.338 --> 22:32.898 Here's women who don't want children, 22:32.900 --> 22:36.890 don't use contraception even though it's available to them, 22:36.890 --> 22:40.760 and yet when they get pregnant they're willing to undergo an 22:40.757 --> 22:42.597 operation, a very crude, 22:42.595 --> 22:46.765 illegal operation by an untrained practitioner that will 22:46.765 --> 22:51.155 lead to a very high rate of death and they're well aware of 22:51.162 --> 22:52.302 that fate. 22:52.298 --> 22:55.608 Everybody knows somebody who's died from a botched abortion and 22:55.609 --> 22:57.959 you've read some of that in the European-- 22:57.960 --> 23:01.920 in the era in America and Europe when that was common. 23:01.920 --> 23:06.440 She went there and it turns out that women are very much 23:06.441 --> 23:09.401 influenced by rumors, what they hear, 23:09.400 --> 23:13.840 because their education is not really their thing. 23:13.838 --> 23:15.888 This student, this Yale undergraduate 23:15.888 --> 23:18.948 collected these rumors, and one of the rumors, 23:18.950 --> 23:23.190 one of the most extreme rumors was well mostly in Africa, 23:23.190 --> 23:26.590 and I think you read this--the people that haven't been to 23:26.589 --> 23:30.109 university don't distinguish between stomach and uterus, 23:30.109 --> 23:31.659 it's all one big cavity. 23:31.660 --> 23:33.270 Was that in one of your readings? 23:33.269 --> 23:36.439 I think it was, anyway it doesn't matter; 23:36.440 --> 23:38.420 it's all one thing there. 23:38.420 --> 23:40.990 Now you take a pill, and they know something about 23:40.988 --> 23:42.588 pills, penicillin and everything, 23:42.594 --> 23:44.344 but every day for the rest of my life, 23:44.338 --> 23:46.378 why do I have to keep taking this pill? 23:46.380 --> 23:49.430 Why don't I take a pill and that settles the issue? 23:49.430 --> 23:54.620 Well they figure I get pregnant and the fetus starts to grow 23:54.615 --> 23:55.665 inside me. 23:55.670 --> 23:57.460 Well what does the pill do? 23:57.460 --> 24:00.390 The pill goes down and dissolves, they have some idea 24:00.385 --> 24:03.705 that it's wet and dissolves, and then reforms over the fetus 24:03.705 --> 24:05.165 and starts coating it. 24:05.170 --> 24:07.830 But everyday they know the fetus is getting bigger, 24:07.828 --> 24:11.428 so you need to take another pill to add to the coat of it, 24:11.430 --> 24:17.700 and at the end what you grow and what you get is a mummy. 24:17.700 --> 24:22.400 You get a fetus that can be fully grown and coated with a 24:22.403 --> 24:26.943 white stuff like an egg and that's what you deliver. 24:26.940 --> 24:29.910 Well if you believe something like that you're not going to go 24:29.907 --> 24:31.317 anywhere near pills, right? 24:31.318 --> 24:36.238 Some of these similar kinds of stories happen with everything 24:36.244 --> 24:36.824 else. 24:36.818 --> 24:40.498 This young lady herself got the five little silastic implants in 24:40.500 --> 24:43.480 her arm and she when she came back she was very-- 24:43.480 --> 24:45.810 she got it in Kenya, one because she wanted it and 24:45.807 --> 24:48.657 two she wanted to show the women sees it's not dangerous, 24:48.660 --> 24:52.860 I'm even doing it myself, but that's irrelevant. 24:52.858 --> 24:57.048 One thing is--any--no clue about medical stuff, 24:57.051 --> 25:00.421 physiology, digestion, anatomy inside, 25:00.423 --> 25:05.623 huge numbers of women don't have any clue about this. 25:05.618 --> 25:10.858 This girl did a very clever thing, she was a Yalie, 25:10.858 --> 25:14.498 and she then asked the women--Kenyan women are not any 25:14.499 --> 25:17.569 stupider than anybody else, they're smart women, 25:17.569 --> 25:19.539 they said do you believe such a rumor? 25:19.538 --> 25:22.978 They were just reporting it as a rumor and the women were of 25:22.981 --> 25:24.851 course very skeptical of this. 25:24.848 --> 25:28.018 Well I've heard this and that is it true or not and they were 25:28.015 --> 25:29.435 properly skeptical of it. 25:29.440 --> 25:31.940 She collected this whole range of rumors, 25:31.940 --> 25:36.430 and she found that--she asked, which ones do you believe more 25:36.434 --> 25:38.884 than others, and she sort of could get a 25:38.884 --> 25:41.454 ranking on it, and then she asked all kinds of 25:41.445 --> 25:44.535 questions and it turned out that it was very simple, 25:44.538 --> 25:47.628 that they believed something depending on how many times they 25:47.634 --> 25:48.414 had heard it. 25:48.410 --> 25:51.480 This particular rumor was not one of the most prevalent, 25:51.480 --> 25:54.190 some other rumors were, equally not true, 25:54.190 --> 25:59.020 but if you hear it a lot then you believe it because they 25:59.019 --> 26:03.499 don't have a sense of expertise, scientific competency, 26:03.502 --> 26:05.302 any of that sort of stuff. 26:05.298 --> 26:08.728 A sociologist at Penn, Susan Watkins, 26:08.730 --> 26:11.660 who I may have mentioned before and certainly will mention again 26:11.664 --> 26:13.534 who works in Kenya in the Luo region, 26:13.528 --> 26:15.288 not in Nairobi, a different region, 26:15.288 --> 26:19.888 she attended a lecture where a local woman, 26:19.890 --> 26:22.300 speaking the local dialect had gone to Nairobi and gotten 26:22.297 --> 26:24.347 trained-- a nurse type--she wasn't 26:24.345 --> 26:27.705 trained--an official nurse-- but working in that kind of 26:27.712 --> 26:31.342 establishment, went to Nairobi and got trained 26:31.343 --> 26:34.733 to be a reproductive health educator. 26:34.730 --> 26:38.130 She comes back and is having some sort of a white coat or 26:38.131 --> 26:40.571 uniform, or a blouse or something and 26:40.574 --> 26:43.114 she gives a lecture to the women with-- 26:43.108 --> 26:45.668 they have these models of pregnancy models, 26:45.670 --> 26:49.570 models of internal anatomy slides, very nice and she was 26:49.567 --> 26:51.907 good at it, and the women were absolutely 26:51.913 --> 26:53.333 rapt, they were listening to every 26:53.327 --> 26:53.557 word. 26:53.558 --> 26:56.728 But as they left the room they started sort of staring each 26:56.728 --> 26:59.208 other, what are we going to make out 26:59.211 --> 27:01.531 of this, and outside there was a woman 27:01.530 --> 27:04.800 scrubbing the floor, a washer woman there and these 27:04.800 --> 27:08.120 women just dove onto the washer woman and said, 27:08.118 --> 27:10.428 is she telling--is what she's telling is true, 27:10.430 --> 27:12.970 is this good for us, is she our kind of women that 27:12.967 --> 27:14.867 the-- and really asked the washer 27:14.871 --> 27:18.301 woman all kinds of questions about this information which the 27:18.295 --> 27:20.745 washer woman had no technical expertise. 27:20.750 --> 27:25.120 The idea being that they don't have this sense of that 27:25.122 --> 27:29.002 knowledge comes from some sort of expertise, 27:29.000 --> 27:31.560 that more knowledge comes from someone like me is a more 27:31.559 --> 27:34.069 important variable than that you've been to Nairobi and 27:34.073 --> 27:35.613 gotten some kind of training. 27:35.608 --> 27:38.178 And the washer woman they perceived was closer to them 27:38.181 --> 27:40.991 than the woman who has gotten some education even though it 27:40.994 --> 27:44.104 was a local-- a person from that local 27:44.096 --> 27:45.136 community. 27:45.140 --> 27:48.850 It's a very complicated issue and the big battle is in getting 27:48.845 --> 27:52.485 people thinking about this and trying to do some of that, 27:52.490 --> 27:58.590 is sort of how much of this difference and how much of the-- 27:58.588 --> 28:01.158 people in general having more--how much of it is that 28:01.164 --> 28:04.094 there's something wrong this data that they really do want a 28:04.086 --> 28:05.966 lot of children and many of them-- 28:05.970 --> 28:11.210 in many countries up there they wanted 5,6, 7,8 children and how 28:11.205 --> 28:16.455 much of it is-- they don't have access--access 28:16.459 --> 28:21.449 doesn't mean just handing out condoms. 28:21.450 --> 28:25.770 This is the last story and I'll shut up. 28:25.769 --> 28:28.779 There's a famous story that passes around family planning 28:28.776 --> 28:31.726 circles about someone going into an African village, 28:31.730 --> 28:36.930 and finding in front of each hut a stick and the stick was an 28:36.930 --> 28:38.490 unrolled condom. 28:38.490 --> 28:41.680 That was very strange and so they went and asked what this 28:41.680 --> 28:41.960 is? 28:41.960 --> 28:45.270 We had a family planning worker and they showed us how to 28:45.265 --> 28:48.745 prevent pregnancy and they had this stick and they showed us 28:48.747 --> 28:51.047 how to unroll it and they did that. 28:51.048 --> 28:54.778 I have heard this kind of story any number of times and I tossed 28:54.778 --> 28:57.098 it off-- it's something like--I had a 28:57.102 --> 28:59.162 little-- the--more doubts, 28:59.163 --> 29:01.733 I just tossed the story off. 29:01.730 --> 29:04.480 Then I'm in Kline Tower and I came out one night, 29:04.480 --> 29:07.050 I work late, and the Forestry was having a 29:07.050 --> 29:10.810 party and some of the graduate students were out back smoking 29:10.813 --> 29:13.673 or chatting, so I chatted them up and one of 29:13.673 --> 29:17.033 them had been in a part of South Africa called Transkei, 29:17.028 --> 29:21.128 and she told me she went into this village and what did she 29:21.134 --> 29:21.564 see? 29:21.558 --> 29:24.728 It was cucumbers and all the people had cucumbers with 29:24.726 --> 29:27.596 condoms unrolled on them, so this is a student who's here 29:27.602 --> 29:29.622 at Yale right now that saw this with her own eyes, 29:29.618 --> 29:33.018 so this is another one of these amazing stories that's true and 29:33.018 --> 29:36.358 gives you sort of at least an anecdotal hint into what's going 29:36.361 --> 29:40.421 on-- scratching beneath this data. 29:40.420 --> 29:42.450 Okay see you next week. 29:42.450 --> 29:48.000