Clear Language, Clear Mind

February 18, 2019

The amazing stereotype accuracy of sex differences in movie genre preferences

Filed under: Stereotypes — Tags: , — Emil O. W. Kirkegaard @ 15:47

This study investigated the accuracy of gender-specific stereotypes about movie-genre preferences for 17 genres. In Study 1, female and male participants rated the extent to which 17 movie genres are preferred by women or men. In Study 2, another sample of female and male participants rated their own preference for each genre. There were three notable results. First, Study 1 revealed the existence of gender stereotypes for the majority of genres (i.e., for 15 of 17 genres). Second, Study 2 revealed the existence of actual gender differences in preferences for the majority of genres (i.e., for 11 of 17 genres). Third, in order to assess the accuracy of gender stereotypes on movie preferences, we compared the results of both studies and found that the majority of gender stereotypes were accurate in direction, but inaccurate in size. In particular, the stereotypes overestimated actual gender differences for the majority of movie genres (i.e., 10 of 17). Practical and theoretical implications of these findings are discussed.

The study didn’t really properly showcase the amazing accuracy of sex stereotypes in their study, but they published their summary stats in a table, so I will help them.

r = .85! The correlation size is not even reported in the paper because they relied on a weird ANOVA approach. While this value might seem very high to you, it is in fact quite common in the study of sex stereotype accuracy. The median of 14 studies recently meta-analyzed was r = 0 .79 (Jussim et al 2018).

The authors conclusion about the stereotypes being larger than the real differences is questionable because they didn’t use the same scale for measuring them. If one wants to investigation the matter of exaggeration — generally not found — one should use ratio scale data which avoids these problems. We did this in our previous stereotype study with immigrant groups in Denmark and found estimation of differences not overestimation (Kirkegaard & Bjerrekær 2016).

September 20, 2018

A note on sex difference in variation in attractiveness

Filed under: Psychology — Tags: , — Emil O. W. Kirkegaard @ 10:02

Given the recent discussion of sex differences in variation in traits, The Audacious Epigone has a quick post based on the GSS (you guessed it). He finds:

The weight finding is probably related to female self-starvation for beauty purposes (anorexia) which creates a stronger left tail for women but not for men. The physical attractiveness is surprising, but I have a guess why. Some years ago, OKCupid famously published some internal data about how sexes rate each other in terms of attractiveness (0-5 scale apparently, though I recall it as 1-5 on the site) and how this is related to contact behavior. It looks like this:

I.e. men rate female attractiveness on a normal curve (close approximation) with a modal/mean/median of close to 2.5, while women’s ratings of men are extremely skewed with a modal rating of 1! OKCupid apparently later deleted the page, but the internet remembers. Anyway, you can now see why male ratings might have less variation — they are all skewed towards the left and the floor effect reduces the variance somewhat. It would be better to obtain machine learning based ratings of men’s attractiveness, and then see if these finds a larger male variation.

January 28, 2017

A sex difference that won’t go away and measurement invariance

Filed under: Differential psychology/psychometrics,intelligence / IQ / cognitive ability — Tags: — Emil O. W. Kirkegaard @ 19:44

Whitley, E., Deary, I. J., Ritchie, S. J., Batty, G. D., Kumari, M., & Benzeval, M. (2016). Variations in cognitive abilities across the life course: Cross-sectional evidence from Understanding Society: The UK Household Longitudinal Study.Intelligence, 59, 39–50. https://doi.org/10.1016/j.intell.2016.07.001

Background
Populations worldwide are aging. Cognitive decline is an important precursor of dementia, illness and death and, even within the normal range, is associated with poorer performance on everyday tasks. However, the impact of age on cognitive function does not always receive the attention it deserves.
Methods
We have explored cross-sectional associations of age with five cognitive tests (word recall, verbal fluency, subtraction, number sequence, and numerical problem solving) in a large representative sample of over 40,000 men and women aged 16 to 100 living in the UK.
Results
Women performed better on word recall tests and men had higher scores for subtraction, number sequence and numerical problem solving. However, age-cognition associations were generally similar in both genders. Mean word recall and number sequence scores decreased from early adulthood with steeper declines from the mid-60s onwards Verbal fluency, subtraction and numerical problem solving scores remained stable or increased from early to mid-adulthood, followed by approximately linear declines from around age 60. Performance on all tests was progressively lower in respondents with increasingly worse self-rated health and memory. Age-related declines in word recall, verbal fluency and number sequence started earlier in those with the worst self-rated health. There was no compelling evidence for age dedifferentiation (that the general factor of cognitive ability changes in strength with age).
Conclusions
We have confirmed previously observed patterns of cognitive aging using a large representative population sample.

A sample of 40,000? How big were the cognitive ability differences by sex? First, the bare tests, and then the g factor.

sex diff UK 1 sex diff uk 2

Eye-balling these gives us a gap of about .25 d that seems very stable. But:

We next tested measurement invariance by sex. A multi-group confirmatory factor analysis showed that a model with configural invariance across the sexes had excellent fit to the data (χ2(8) = 283.81, p < 0.001, RMSEA = 0.041, CFI = 0.993, TLI = 0.981), as did a model with weak invariance (χ2(12) = 476.23, p < 0.001, RMSEA = 0.044, CFI = 0.988, TLI = 0.979). However, the model with strong invariance had poorer fit (χ2(17) = 3668.12, p < 0.001, RMSEA = 0.103, CFI = 0.902, TLI = 0.884); indeed, the model with only configural invariance had significantly better fit than either the weak (χ2(4) = 192.42, p < 0.001, ΔAIC = 184.42, ΔBIC = 149.96) or strong (χ2(11) = 3384.32, p < 0.001, ΔAIC = 3366.32, ΔBIC = 3288.78) invariance models. Thus, there was evidence that the g-factor of cognitive ability had different structure across the sexes.

In human language, what does this mean? We have to remember what measurement invariance is. I quote from Alexander Beaujean‘s textbook:

1. Configural. This is the most basic level, and just indicates that LVMs have the same structure in all the groups. That is, the groups have the same number of LVs, formed by the same number of indicator variables, all of which have the same pattern of constrained and estimated parameters. There is no requirement that any estimated coefficients are equal across groups, but the price for these weak assumptions is that there is no reason to believe that the LVs are measuring the same construct in each group. Thus, this level of invariance does not warrant any between-group comparisons of the constructs the LVs represent.

2. Weak. This level adds that, for a given indicator, the loadings are the same across groups. Latent variances are allowed to vary among groups, though. With weak invariance, there is a weak argument that the LVs are equivalent between groups, but, at most, this condition only allows a comparison of the latent variances and covariances.

3. Strong. This level of invariance adds the constraint that, for a given indicator variable, the intercepts are the same among groups. When constraining the intercepts, the latent means are allowed to vary among groups. With this level of invariance, individuals at the same level of a given LV have the same expected value on the indicator variables, irrespective of group membership. Moreover, strong invariance allows for comparisons of the LV. Specifically, latent means, variances, and covariances can all be compared among groups. If there are group differences on strongly-invariant LVs, it likely indicates that there are real difference in these variables, as opposed to the difference being in how the LVs are measured.

4. Strict. This level adds that, for a given indicator, the error variances are constrained to be equal across groups. Usually this level of invariance is not required for making cross-group comparisons of the LVs. Because the error terms in a LVM are comprised of random error variance as well as indicator-specific variance, there is not necessarily the expectation that they would be the same among the groups. Thus, this form of invariance is usually tested, in conjunction with evaluating invariance of the latent variances (level 5), when the area of interest is the reliability of the construct the LV represents. If the latent variances are invariant among the groups, then evaluating strict invariance is really an investigation of construct reliability invariance.

5. Homogeneity of Latent Variable Variances. The variance of a LV represents its dispersion, and thus represents how much variability there is in the construct that the LV represents varies within groups. If there is homogeneity of the latent variances, this indicates the groups used equivalent ranges of the construct for the indicator variables’ values. If this does not hold, however, this indicates that the group with the smaller amount of latent variance is using a narrower range of the construct than the group with the larger amount. Evaluating homogeneity of latent covarinaces can be done, too, but there is usually not much to be gained from such an analysis.

6. Homogeneity of Factor Means. This level of invariance indicates no differences among groups in the average level of the construct the LV represents. Like the more traditional analyses of mean differences (e.g., ANOVA), if there is more than one group then the test of a latent variable’s mean differences usually begins with an omnibus test that constrains the means to be equal across all groups. If this model does not fit the data well, then subsequent tests may be conducted to isolate specific group differences.

Latent variable models (with reflective factors at least) work by positing an unobserved variable (latent, factor) that account for the observed relationships between tests. In this case, we only have 5 tests and we posit a g factor to account for their intercorrelations. In this setting, what it means to say that strong measurement variance fails is to say that when we regress (try to predict) the test scores on our tests from the score on the posited g factor, is that the intercepts in the regressions are not the same by sex.

My guess is that the intercept bias/invariance has to do with the composition of the battery. There were only 5 tests, and their breakdown was: 3 math, 1 verbal, 1 memory. Women had better memory but there was no difference in verbal fluency (this is a common finding despite what you have been told). So, the problem likely is that the g factor is colored because 60% of the tests were about math, and that men have an advantage on the math group factor. Since the math group factor was not modeled here (and could not due to too few tests), it shows up as intercept bias for the g factor. This is omitted variable bias. This is also present for e.g. SAT, where women get higher GPA than their SAT scores predict. That’s because they have an advantage in personality (conscientiousness/study habits) that isn’t modeled. Simulation here: http://emilkirkegaard.dk/understanding_statistics/?app=test_bias_omitted_variable_bias

In fact, the data for this study are quasi-public. I was able to get them in a few minutes. Not mentioned by the authors is that there are item level data for the cognitive tests. But they didn’t give the same items to everybody, so the data are not easy to analyze (have to analyze subsets with complete data or merge items with assumed equal properties (what the authors did)). For instance, wave 3 (the subset the authors analyze) has 3,022 variables alone. About 400 of these have to do with the cognitive testing. They are not all about whether someone got an item right or wrong, but about things such as whether the interviewer thought that the subject was stressed or anxious during testing. I was able to do some rudimentary analyses to confirm the findings. I only used the subtraction, fluency and numeric ability data because these were easy to work with. They produced a fairly skewed distribution due to lack of difficult items.

g_dist

The age pattern for the g factor (actually I averaged the z scores using equal weights).

g_age_sex

And if we remove age by LOESS:

g_noage_sex

g_dist_sex

The standardized difference is .22 d, or 3.3 IQ using this method.

The results present something of a dilemma for the blank slaters. They must either accept that there is a difference in g for a very large sample of mostly UK Whites and that this was almost entirely stable over an age span of 70 years or so. Or they can say that the test has a biased composition and the g biased, and that is correct I think, but this just means that men instead have an advantage in mathematical ability that is just as consistent across the age span as the g one. In fact, men may have both.

The very strong stability of results across such an age span makes the results very hard to explain in terms of unequal education, stereotypes etc. There have been large social changes for women over the last 70 years, but about none observable in the age pattern. Hence, it is unlikely that the difference is due to these changing social factors.

The million dollar question is: How do we square this with results from very large Romanian study? It used good quality tests and had a sample size of 15,000. So, as far as tests go, the Romanian study wins. As far as sample size goes, the British study wins. Perhaps the g difference observed here was entirely due to battery composition. Or perhaps there are cross-population differences in sex differences in cognition (as argued e.g. by Davide Piffer).

For those wondering if the data are useful for country of origin analysis. The answer is no. There are variables for country of origin (good, captures first generation) and mother/father’s country of origin (very good, captures second generation and mixed origins), these variables have almost no data. As in, 200 datapoints for a sample of 60k persons. Maybe I missed something and I will have to take a closer look at a later point (i.e. probably never).

September 16, 2016

Academic fields and gender: 13 years before ‘Perceptions of Brilliance’

http://rpubs.com/EmilOWK/209727

plot

 

October 8, 2015

Email exchange with ‘cognitive neuroscience researcher’ Jayl Feynman

Filed under: Differential psychology/psychometrics — Tags: , , — Emil O. W. Kirkegaard @ 22:59

Some readers may have fun reading this. I have not edited anything. Due to the conversion some extra lines were added, but his emails genuinely contains lots of oddly placed line breaks. The odd use of e.g. bold is his (Jayl is a male name, apparently).

The topic of the email is “University of Toronto, Canada”.


Jayl Feynman <feynmantoronto@outlook.com> 5. oktober 2015 kl. 23.01
Til: “emil@emilkirkegaard.dk” <emil@emilkirkegaard.dk>
I am a cognitive neuroscience researcher from Toronto and wanted to make comment if you don’t mind on one of your studies titled “Sex differences in g and chronometric tests

Study –  file:///C:/Users/user/Downloads/article2.pdf

Males average 100g more brain than women, and brain size is known to correlate with general intelligence (g), leading to the possibility that men average somewhat higher in g than women

Intelligence is a reflection of the efficacy of the networks responsible for cognition and not merely the absolute size of the human brain. Hence it’s quality over quantity. The best model for predicting the neuroscience of intelligence is the P-Fit theory which you could read about it here:

http://www.livescience.com/1863-theory-intelligence-works.html

The P-Fit theory also contradicts the claim that G factor does not change as Parietal-frontal integration changes through experience and connectivity.

It has also been shown that brain size correlates with IQ with a strength of about .38
Correlation is not causation. Even Einstein’s brain was smaller than average:

A critique of IQ testing

 
1. IQ tests such as Raven progressive matrices are very much flawed because almost all of the questions are spatial in nature (picture completion,block design etc)  and do not really touch on the verbal part of intelligence. To date, I have never seen an IQ test that measure verbal comprehension or fluency Measuring spatial ability also cannot be predicative in measuring ability in comprehending literature, novels, books and just about everyday language use.
2. Psychologists do not distinguish between different forms of information when measuring IQ. Different forms of information such as spatial and verbal information uses different areas of the brain for example pictures shapes and even arithmetic or digits use an area of the brain known as the Parietal lobe. Numeracy and digits which Psychologists think are verbal  actually happens to be spatial since the brain represents them as  quantity of space through mental imagery. Verbal information on the other hand such as words, sentences, language and meaning are processed by two areas of the brain known as Brocha’s and Wernicke’s area. Therefore IQ does not measure verbal intelligence especially in processing, reasoning and understanding the use of language.
3. Sample restriction and recruitment bias. The methods in which members of the each group enter the study sample is not in the control of the investigator in charge of the study. For example, in college or school studies it could easily be that both average and less average females enter the study while higher level males enter the study. This would obviously obscure mean differences.

4. Variability hypothesis and bias. This hypothesis holds that males exhibit greater variation than females in many cognitive ability domains, which may explain their overrepresentation in the tails of ability distributions and creates the appearance of mean differences in incomplete or selected samples. The male variability is obviously higher in the right tail of college samples therefore college sex differences in IQ is inaccurate in measuring IQs of the general population.

5. Intelligence is an emergent property of anatomically distinct networks of the brain each of which has it’s own distinct capacity. Therefore to measure general intelligence one would have to measure the distinct capacity of each brain network on which a singular IQ testing cannot do. You would need multiple separate tests to measure the capacity of each network.

 

Emil Ole William Kirkegaard <the.dfx@gmail.com> 6. oktober 2015 kl. 02.36
Til: Jayl Feynman <feynmantoronto@outlook.com>
Jayl,

I googled your name yet was unable to find anything about your academic standing. LinkedIn is the only result and states that you are “Entrapreneur at MySelf (as an independent consultant)”. There is no mention of your name on the university website and I could locate no publications in your name on Google Scholar. The only things that come up are the publications of a physicist doing work on e.g. solar physics. Your email comes from a non-university address whereas academics usually use their institutional email. They also usually have a signature, whereas you have none.

So, taken all together, the evidence seems to show that you are not who you say you are. I’ll make the assumption that you are a random internet person who is uncomfortable with sex differences in cognitive ability. After all, many people are.

Anyway, I will reply, just for fun. :)

The paper you ‘link to’ (actually you gave the file’s location on your own computer) is a submission that was never published. You can read the submission thread to see why. http://openpsych.net/forum/showthread.php?tid=9

Intelligence is a reflection of the efficacy of the networks responsible for cognition and not merely the absolute size of the human brain. Hence it’s quality over quantity. The best model for predicting the neuroscience of intelligence is the P-Fit theory which you could read about it here:
Correlation is not causation. Even Einstein’s brain was smaller than average:

Why do you presume I don’t know what P-FIT is? If so, linking me to unreliable secondary sources is even more strange. Good rule of thumb: if you want to introduce a researcher to something, cite the primary literature. In this case:

Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral and Brain Sciences, 30(02), 135-154.

There are also some newer relevant work, e.g. by Roberto Colom.

In any case, I don’t think anyone made the claim that size explains all variation in cognitive ability, only that it explains some of it. Given the evidence, it would be extremely surprising if it did not. The very thing that makes humans unique is their high cognitive ability which increased over recent evolutionary time along with the brain size (i.e. we see it by increasing skull sizes; relative to body size).

If brain size was a non-causal correlate, one has the odd job of explaining why it was selected for by evolution just over the same time span. Note that brain tissue is extremely metabolically expensive. The brain accounts for about 20% of the rest metabolic rate yet takes up only about 2% by weight. Increased brain size causes substantial problems with childbirth which kills off a large number of women. A non-causal theory is that evolution still selected for larger brains despite all these costs. Presumably, this is why pretty much no one serious subscribes to that idea.

As for Einstein’s brain. You are citing a single case which cannot disprove an imperfect correlation, so the case is a non-starter. In this case, the case has an obvious explanation: the brain shrinks as we age (matching the decline in absolute scale cognitive ability).

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2596698/

The P-Fit theory also contradicts the claim that G factor does not change as Parietal-frontal integration changes through experience and connectivity.

No one claims a stability of 1 for GCA, hence change in brain structure is clearly consistent with relatively stable GCA. Also note that our measures of GCA measure relative standing (they are deviation scores), not absolute ability. So in fact, no change in GCA is consistent with change in the underlying brain structure if all members of the cohort have the exactly same brain changes (this isn’t true, but I’m just pointing it that the argument to be valid, needs this unstated premise).

This looks to be the stuff you really wanted to say. IQ criticism.
1. IQ tests such as Raven progressive matrices are very much flawed because almost all of the questions are spatial in nature (picture completion,block design etc) and do not really touch on the verbal part of intelligence. To date, I have never seen an IQ test that measure verbal comprehension or fluency Measuring spatial ability also cannot be predicative in measuring ability in comprehending literature, novels, books and just about everyday language use.

2. Psychologists do not distinguish between different forms of information when measuring IQ. Different forms of information such as spatial and verbal information uses different areas of the brain for example pictures shapes and even arithmetic or digits use an area of the brain known as the Parietal lobe. Numeracy and digits which Psychologists think are verbal actually happens to be spatial since the brain represents them as quantity of space through mental imagery. Verbal information on the other hand such as words, sentences, language and meaning are processed by two areas of the brain known as Brocha’s and Wernicke’s area. Therefore IQ does not measure verbal intelligence especially in processing, reasoning and understanding the use of language.

In fact, RPM does not have picture completion or block design. These are both subtests of the WAIS.

You say you have never seen an IQ test measuring these, which means that you have not looked hard because WAIS, probably the most widely used test of all, has a an entire subscale called verbal comprehension consisting of 3-4 tests, depending on which version of WAIS.

http://images.pearsonclinical.com/images/assets/WAIS-IV/WAISIV2_6_08.pdf

The last claim about lack of cross-area predictive validity is widely known to be false. Indeed, it has been known for decades, even going back to Spearman’s time in the 1930s. This is what is called indifference of the indicator, it doesn’t matter that much just which mental test is used to assess GCA, as long as the g-loading is strong, the predictive validity will be similarly strong. A great general resource is still:

Arthur Jensen. 1980. Bias in Mental Testing.

3. Sample restriction and recruitment bias. The methods in which members of the each group enter the study sample is not in the control of the investigator in charge of the study. For example, in college or school studies it could easily be that both average and less average females enter the study while higher level males enter the study. This would obviously obscure mean differences.

4. Variability hypothesis and bias. This hypothesis holds that males exhibit greater variation than females in many cognitive ability domains, which may explain their overrepresentation in the tails of ability distributions and creates the appearance of mean differences in incomplete or selected samples. The male variability is obviously higher in the right tail of college samples therefore college sex differences in IQ is inaccurate in measuring IQs of the general population.

Sometimes the researcher do get to decide, especially when they collect their own data. Other times, they use available datasets which may have recruitment bias. The fact that you cite research written by top researchers (Earl Hunt, Ian Deary) in the field discussing this means that they are aware of the problem.

In any case, there are general population samples too that find differences in variance and some that do not, same as for mean differences. This is why the question is currently undecided.

http://drjamesthompson.blogspot.com/2013/09/are-girls-too-normal-sex-differences-in.html

5. Intelligence is an emergent property of anatomically distinct networks of the brain each of which has it’s own distinct capacity. Therefore to measure general intelligence one would have to measure the distinct capacity of each brain network on which a singular IQ testing cannot do. You would need multiple separate tests to measure the capacity of each network.

You seem unaware of the g factor and seem to posit something like the Thompson’s sampling theory. The networks are not independent and attempts to make tests that do note correlate have all failed despite decades of attempts. Maybe read:

In any case, WAIS does try to measure a diverse set of cognitive abilities. This is a good idea because it results in a better measurement of GCA, which is what is responsible for the validity of the tests. See review at:

http://emilkirkegaard.dk/en/?p=4581

-Emil

 

Jayl Feynman <feynmantoronto@outlook.com> 6. oktober 2015 kl. 04.20
Til: Emil Ole William Kirkegaard <the.dfx@gmail.com>
 “The very thing that makes humans unique is their high cognitive ability which increased over recent evolutionary time along with the brain size (i.e. we see it by increasing skull sizes; relative to body size)

Actually our overall brains have been shrinking for the past 30,000 years.
http://phys.org/news/2011-02-brains-smarter.html

On the other hand, our frontal lobes are growing and have gotten much bigger.

 
The prefrontal cortex is slightly larger relative to the rest of the brain in humans than in most other primates while also having larger volume of white matter to go alongside within it.
http://thebrain.mcgill.ca/flash/a/a_05/a_05_cr/a_05_cr_her/a_05_cr_her.html

As for brain relative to body size, humans have the same as a mouse.  The size of  specific brains areas (prefrontal cortex, hippocampus, parietal cortex etc) specified by the P-Fit, are better correlations for intelligence than overall brain size.

“If brain size was a non-causal correlate, one has the odd job of explaining why it was selected for by evolution just over the same time span”
 

Because bigger brains equals to more lateralization (asymmetry) of brain functions.

file:///C:/Users/user/Downloads/fnhum-08-00915.pdf

 Lateralized brain allows dual attention to the tasks of feeding (right eye and left eye hemisphere) and vigilance for predators (left eye and right hemisphere). Hence it was most likely selected because dual attention was an advantage for human survival.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973910/

 

Jayl Feynman <feynmantoronto@outlook.com> 6. oktober 2015 kl. 06.03
Til: Emil Ole William Kirkegaard <the.dfx@gmail.com>
Also, I see you have been following this study:

http://emilkirkegaard.dk/en/wp-content/uploads/Males-have-greater-g-Sex-differences-in-general-mental-ability-from-100000-17-to-18-year-olds-on-the-Scholastic-Assessment-Test.pdf

Using SATs to generalize about the broader population is hardly reasonable. Out of 3.3 million high school graduates per year, only 1.3 million take the SATs while only 65% of those 3.3 million actually enroll in college. It seems the SATs are probably just male variance in effect.

 

Jayl Feynman <feynmantoronto@outlook.com> 8. oktober 2015 kl. 22.54
Til: Emil Ole William Kirkegaard <the.dfx@gmail.com>
So you didn’t respond huh? Well then I will just end with this, after I looking over different test samples I have come to the conclusion that IQ tests are nonsense. The questions are almost all spatial in nature while having a quantitative and visuo-spatial section is redundant as they both measure mental rotation and spatial visualization. IQ test should thus be re-named SIQ or Spatial intelligence quotient because that is precisely what it measures. School academics are probably better predictors for future success more than this pop quiz. So I guess psychology have been getting it wrong for the last 100 years, but what can you expect from a field of study that only looks for correlations right? Well you can find correlations in anything for example I correlate with Psychology with bigotry since it produce the most out of any field example Rushton, Lynn and probably you.

Chao :P

 

I guess he thinks e.g. these are spatial items:

verbal items logical itemssyntactic

(All from Jensen’s Bias in Mental Testing).

The criticism is particular odd because I already told him about the actual composition of the WAIS.

Notice the links to files on his own computer. The same novice computer mistake made by the feminists writing for the UN.

I was not able to find the source paper for the claim that brain sizes got smaller during the last 30kya period. Can someone find it? Did body size shrink as well? If so, then brain-to-body size ratio may have increased over the period, or stayed the same.

I haven’t heard of the brain size evolved due to lateralization hypothesis before, but the review article he linked to seems interesting: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973910/

The real reason I didn’t reply was that I was busy traveling home from the USA to Denmark. Still, it doesn’t seem worth my time.

January 4, 2015

The inconsistency of studies of gender differences in cognitive abilities: due to using different methods?

I read this study:

Palejwala, M. H., & Fine, J. G. (2015). Gender differences in latent cognitive abilities in children aged 2 to 7. Intelligence, 48, 96-108.
It reminded me that these studies rarely test what happens when one uses a bunch of different methods on the same dataset. Nyborg (2003) wrote years ago that different results were probably to a high degree due to this. There seems to have been no change in research practices since then.
Due to the lack of data sharing, it is generally not possible for researchers inclined to perform a such study on the data they used. One is limited to either gathering some data oneself or finding some open dataset.
Wicherts and Bakker (2012) have provided researchers with an open dataset. It is not at all perfect: unrepresentative; psych students, young and mostly female, and medium-sized; N=400-500 (depending on treatment of missing data).
Obviously, the study cannot be used to determine the size of any difference in the general population. However, it should be sufficient for researchers to see how different methods compare. One can try summing latent variables. One can use EFA in various ways (different extraction methods, Schmid-Leiman transformed or not, hierarchical or not) to extract latent traits and compare the score means and variances. One can do it with CFA/SEM with different models (hierarchical, bi-factor). How would all these results compare? The data is public, so who wants to do this study with me?
The closest study of this kind is maybe Steinmayr et al 2010. But it used non-public data, and did not use all the available methods. For instance, it did not use latent models with a g factor at all, only 5 primary factors (?!).
The above is not to say that using different samples does not alter results too. There are various ways of excluding participants, e.g. for handicaps (fysical, mental, both) which surely change both means and variances. Worse, most data concern only a rather small number of subtests (because they rely on commercial tests, also bad!) which were often picked to minimize gender differences (or at least balance them out which means that total summed score is useless).
It would be better if some super/master dataset could be collected with say 60 very different mental tests: elementary cognitive tests, Piagetian (do these work on adults? or too strong ceiling effect?), matrix, vocabulary, number series, picture completion, analogies, digit span, learning tests, maze solving, get inspiration from Jensen (1980, Chapter 4), … with a minimum of 3 per type of test so a latent group/type factor can be estimated if one exists) and then all researchers could study the same dataset. This is how science should work. Methods and data must be completely open.
Refs
Nyborg, H. (2003). Sex differences in g. The scientific study of general intelligence, 187-222.
Wicherts, J. M., & Bakker, M. (2012). Publish (your data) or (let the data) perish! Why not publish your data too?. Intelligence, 40(2), 73-76.
Jensen, A. R. (1980). Bias in mental testing.
Steinmayr, R., Beauducel, A., & Spinath, B. (2010). Do sex differences in a faceted model of fluid and crystallized intelligence depend on the method applied?. Intelligence, 38(1), 101-110.

August 25, 2014

Review: Is there anything good about men? (Roy F. Baumeister)

Filed under: Evolutionary Psychology — Tags: — Emil O. W. Kirkegaard @ 15:52

http://www.goodreads.com/book/show/8765372-is-there-anything-good-about-men

http://gen.lib.rus.ec/book/index.php?md5=B21C5698CE12510CDEDBE940259BDF6F

If you read the original essay, there is not much to recommend about the book. It taught me very little, has no data tables, no plots, no figures. Numbers are only mentioned in the text and sources are only given in the back of the book. There were a few interesting works mentioned, but basically the book is just a longer and more repetitive version of the essay.

Hard to say whether to give this 2 or 3 stars. Generally the author has truth on his side. Perhaps 3 then.

September 12, 2013

Review: Taking sex differences seriously (Steven E. Rhoads)

Filed under: Evolutionary Psychology,Psychology,Sociology — Tags: , — Emil O. W. Kirkegaard @ 22:45

http://bookos.org/s/?q=taking+sex+differences&t=0

This shortish book contains a wealth of information and 100s of citations. Unfortunately, the author has not kept a high standard of citing things, nor does he make it clear when he cites something less reliable. This makes it the case that one cannot just take the points for granted and have to check every interesting but potentially dubious claim.

I thought chapters 1-3 were the most interesting, as it was about the science of sex differences. The least interesting part was the one about fatherless families. Pretty much all he cites is a lot of correlational studies, and does not discuss the methodology either.

Its worth a read if one is interested in a huge collection of sex differences, but its not a good introduction to the science of that area. For that, try David Buss’s introduction to evolutionary psychology instead.

In 1966, a botched circumcision left one of two male identical

twins without a penis. A leading sex psychologist, Dr. John

Money of Johns Hopkins University, persuaded the parents to

raise the toddler as a female. When the child was twenty-two months

old, surgeons castrated him and constructed what appeared from

the outside to be female genitalia. Called Brenda and treated like a

girl, the child was later prescribed female steroids to “facilitate and

mimic female pubertal growth and feminization.”1

When Brenda was twelve, Dr. Money reported that she and

her parents had adjusted well.2 The media loved the story of the

“opposite-sex identical twins.” In a long report, Time magazine

called the case “strong support” for the view that “conventional

patterns of masculine and feminine behavior can be altered.” The

1979 Textbook of Sexual Medicine noted the girl’s “remarkably

feminine” development, which was taken as demonstrating the

flexibility and “plasticity of human gender identity and the rela-

tive importance of social learning and conditioning in this

process.”3

In academia, numerous introductory psychology and sociol-

ogy texts used the case to argue that sex roles are basically learned.4

Theorists who believed that gender roles are socially constructed

were ecstatic. In 1994, Judith Lorber described how the girl’s par-

ents “bent over backwards to feminize the girl and succeeded. Frilly

dresses, hair ribbons, and jewelry created a pride in looks, neatness

and ‘daintiness.’” The social construction of gender, she concluded,

“overrode any possibly inborn traits.”5

In retrospect, one wonders whether it is fair to say that what

happened to Brenda was simply “social construction.” With the injec-

tion of female hormones and without the male hormones coming

from testicles, Brenda was getting a bit more encouragement toward

femininity than families and society usually administer. Nonethe-

less, when the facts became more accurately known, it was clear

that neither the chemicals nor the socialization efforts had succeeded

in making Brenda a girl. Some hardworking researchers and jour-

nalists were able to show that Dr. Money had completely misrepre-

sented the results of his experiment. In the early 1990s, they located

the grown-up Brenda and found that she was now named David,

working in a slaughterhouse, married to a woman, and the adop-

tive father of three children.6 At age fourteen, Brenda had decided

to start living as a male, and at fifteen, she had been told the truth

about her biological past. She then announced that she had always

felt like a male and wanted to become one again. She was given a

mastectomy, male hormones and a constructed penis.

The story that emerged revealed that David had always acted

like a male even when everyone in his world had told him he was a

female and should behave like one. The first time “Brenda” was put

in a dress, she pulled it off. When given a jump rope, she tied people

up or whipped them with it. At nine, she bought a toy machine gun

when she was supposed to buy an umbrella. The toy sewing machine

went untouched; she preferred to build forts and play with dump trucks.

She rejected cosmetics and imitated her dad shaving. On a trip to New

York, she found the Rockettes to be sexy. She wanted to urinate stand-

ing up. On the playground, her kindergarten and elementary school

teachers were struck by her “pressing, aggressive need to dominate.”7

As the real story of the reconstruction of David was made pub-

lic, responsible researchers on the Johns Hopkins medical staff

decided they should find out what had become of the many boys

born without penises, most of whom had been castrated and sub-

sequently raised as girls. Of twenty-five located (ranging in age from

five to sixteen), every single one exhibited the rough-and-tumble

play more characteristic of boys than girls. Fourteen had declared

themselves to be boys, in one case as early as age five. Two children

were found who were born without a penis but had not been cas-

trated or sexually reassigned. Both these children, raised as boys, fit

in well with their male peers and “were better adjusted psycholog-

ically than the reassigned children.”8

On hearing this Johns Hopkins paper, Dr. Margaret Legato, a

Columbia University professor of medicine and an expert on sex-

ual differentiation, asserted: “When the brain has been masculin-

ized by exposure to testosterone [in the womb], it is kind of useless

to say to this individual, ‘you’re a girl.’ It is this impact of testos-

terone that gives males the feelings that they are men.”9

Im surprised it didnt work better than it did. This is a huge change in environment and hormonal levels, even castration. Nature is stubborn, very stubborn.

Other writers whose approach to gender has been influenced

by biology have more directly blamed feminists for ignoring or belit-

tling good science on sex differences.22 But the other side replies that

some of the sociobiological literature is filled with “sexism,” “biased

selection of examples” and “a social construction of gender that is

relatively independent of the facts.”23 Mainstream feminists regu-

larly charge that a hidden or not so hidden agenda meant to pre-

serve male status lies behind the sex difference research.24

Feminists who make charges of this kind are often remarkably

candid in declaring that their politics influence their scientific judg-

ments. Thus Anne Fausto-Sterling admits to demanding “the high-

est standards of proof . . . on claims about biological inequality.”25

Sheila Tobias, author of Overcoming Math Anxiety, says she does

research on girls and math to get the truth, but also to get the coun-

try to believe that girls have the potential to perform equally with

boys.26

Ah, the difference of standards of evidence. https://en.wikipedia.org/wiki/Moving_the_goalposts

Note that this is not grounded in any claims about it being extraordinarily claims, and thus having a low prior and thus needing stronger evidence to get P>0.5.

Today, however, the majority of the sex difference researchers

who focus on biology are women. In preparing his book on sex dif-

ferences, Robert Pool read widely and spoke to many researchers

in the field, and was struck by the fact that this research fraternity

was “really a sorority. Most of the scientists doing the provocative,

ground-breaking research into human sex preferences are women.”

This seems to be for two reasons: First, men are wary about pub-

lishing any findings that might bring charges of sexism. Second,

some female researchers seem to have been suspicious about what

their male colleagues were up to; these women say they got involved

because they believed that male researchers were neglecting the seri-

ous study of women. Others did so because they were intrigued and

troubled by some differences favoring men and they wanted to find

out what could explain these results.37 Pool finds that almost all of

these female researchers “identify themselves as feminists or at least

sympathize with feminist goals. . . . They are not fools or tools of

male-dominated society, nor do they have any hidden agendas, and

they uniformly resent such implications.”38

Many of these female researchers also began their studies con-

vinced that sex differences were minimal and that societal forces

caused those that existed. John Williams and Deborah Best, for exam-

ple, began their international comparison of stereotypes believing

there was no basis for them, but concluded that they had “a substan-

tial degree of behavioral validity” and were explained in part by biol-

ogy.39 Similarly, Diane Halpern intended to demonstrate that any

gender differences in cognition were the result of “socialization prac-

tices, artifacts and mistakes in the research, and bias and prejudice.”

After reviewing a pile of journal articles that stood several feet high

and numerous books and book chapters that dwarfed the stack of

journal articles, I changed my mind. . . . [T]here are real, and in some

cases sizable, sex differences with respect to some cognitive abilities.

Socialization practices are undoubtedly important, [sic] there is also

good evidence that biological sex differences play a role.40

It is not usually pleasant to change one’s mind about core convic-

tions, but these researchers say the data has forced them to do so.41

Eleanor Maccoby’s research has led her to give more emphasis to

biology in her study of children. In a recent lecture, after noting the

stereotypical pattern of young boys’ and girls’ fantasy stories (Bat-

man and the like for boys, brides and ballet for girls), Maccoby told

her audience of fellow academics, “I too want to say, ‘ugh.’”42 But

the truth was the truth.

Nature really is stubborn.

Many other male hobbyists, like the Battlebot community of

technonerds, have interests that focus on machines or war. There

are the car enthusiasts, the model train lovers, the war board-game

connoisseurs, the Civil War buffs. These hobbyists are single-minded

about what they love; and studies have found single-mindedness

and a highly focused brain to be more characteristic of men than

women.107

This seems like an interesting claim, it is especially related to geniuses, of which there is an extreme sex ratio. Note 107 leads to: Moir, 1999, pp. 253–55; Lubinski et al., 1993, p. 702.

which leads to

Moir, Anne, and Bill Moir. 1999. Why Men Don’t Iron. New York:

Citadel Press.

Lubinski, David, C. P. Benbow and C. E. Sanders. 1993. Reconceptu-

alizing Gender Differences in Achievement among the Gifted. In

International Handbook of Research and Development of Gifted-

ness and Talent, ed. K. A. Heller, F. J. Monks and A. H. Passow.

London: Pergamon Press.

unfortunately, these are both books so i cant look them up easily.

In 1975, the California Department of Education went so far

as to reject reading texts with any portrayal of women in a house-

hold role. The publisher Open Court appealed the rejection of its

reading texts, which had already been revised to meet standards of

gender equality. (The publisher noted that California bureaucrats

had even complained about a brief reference to Mother Hubbard.)145

Open Court made little headway. In later editions of the text, for

example, The Little Engine That Could became female.

It may be time to start questioning the assumption that soci-

ety pressures young women to be homemakers. My observations of

bright University of Virginia students suggest that they feel pres-

sured in other directions entirely. I remember one young woman

with a 3.8 grade point average in economics who told me how furi-

ous she was at her economics professors. When she told them she

loved children and wanted to be an elementary school teacher, they

let her know they were disappointed—she could do so much more.

I encounter feminist students who seem to have absorbed all

of their teachers’ opinions but whose hearts appear to be at war

with their opinions. In class they are sure that women would be

physicists and engineers—or, at the very least, have demanding

careers of some kind—if it were not for discriminatory socializa-

tion. I remember one of my students who openly declared that she

was looking for a husband who would be the “wife” so she could

quickly advance in her career. But when our discussion meandered

into the popularity of romance novels, she said she read them all

the time. When I expressed surprise and asked why she would pur-

chase so many books filled with powerful and worldly heroes and

spirited but traditional heroines, she said, “Lots of things I do have

nothing to do with what I spout around campus all day.”

Indeed, the effect of the environment is proved to be of smaller importance, since women are routinely exposed to these anti-traditional stories, and yet they still prefer natural gender roles. Nature triumphs over environment here.

It is not surprising, though, that women everywhere seem to

care very much about how they look. In Syrian universities, women

attending classes with men spend as much time dressing for classes

as American women spend dressing for a dinner party. On the streets,

demure Muslim girls in head scarves practice a “below the knees

exhibitionism” with sheer stockings and sling-back heels beneath

their skirts.90 A student who spent a summer in a small Jordanian

city confirms that when Islamic women are not allowed to show

hair or ears and when they wear their skirts to their ankles, they use

more makeup than Western women do and spend more time on

pedicures. A recent study examining the self-images of Iranian-born

women living in Los Angeles and Tehran found that the latter group,

largely unexposed to Western media and required to wear body-

encasing clothes, were nonetheless more concerned about their weight

and more dissatisfied with their bodies, on average, than were the

women living in Los Angeles.91

We will see in the next section that men also have to compete,

in those areas that women care about. Still, it seems unfair, in some

cosmic sense, that men can attract women in different ways—through

success in politics, business, sports or music, for instance—whereas

for women so much depends on how they look. As a thoughtful author

of a book on beauty puts it, “Every woman finds herself, without her

consent, entered into a beauty contest with every other woman.”92

As long as men love female beauty, women will care about

their appearance. And the “male gaze” so often attacked bySex 61

mainstream feminists will continue to please as well as annoy. As a

younger woman, writer Anne Roche Muggeridge hated the street

taunts and the “horrid, cold-faced girl-watching in school corridors

and pubs.” But, like most women, she enjoyed being “approvingly

noticed.” She even liked—“very much” liked—the clearest sign of

such notice, the wolf-whistle:

Girls don’t know whether they are pretty or not. They stand in despair

in front of their mirrors and wail to their mothers: I look so ugly!

[Mothers reassure,] and the daughters don’t believe it. But when a

group of young, handsome male strangers spontaneously burst into

a chorus of admiring notes, a girl must, even in her confusion and

diffidence, experience a glow of pleasure and a dawning self-

confidence.

Muggeridge wishes she were still in “the being-whistled-at age

bracket.”93 Other women approaching their fifties also feel a loss

because men no longer gaze at them in “that safe but sexual kind

of way.”94 Indeed, feminists such as Germaine Greer are among those

who have complained about becoming invisible to men as they grow

older.95

It is impossible to please these women. Damned if u whistle, damned if u dont…

It also reminds me of a similarly natural but irrational man thing: trying to impress prostitutes. https://maggiemcneill.wordpress.com/2013/03/26/book-review-superfreakonomics/

A few years ago, a student brought me a romance novel, Laura

Taylor’s Anticipation, that was used in her course on women’s lit-

erature. She said the climactic scene appeared to her to be a rape.

In it Spence declares that Viva and he will marry, and Viva asserts

they will not. Her blue eyes flash as she walks out of the room toward

her bedroom. He follows, relieves her of her wine glass, and smiles

at the outraged expression on her face. He scoops her up and deposits

her on the bed while shedding his clothes in record time. She glares

at him and says, “Are you deaf?” He gently topples her on her back.

Leaning over her, he efficiently jerked the front of her caftan apart,

sending dozens of buttons flying every which way, then stripped it

off her body.

What do you think you are doing?” she demanded as she glared

at him.

He watched her nipples tighten into mauve nuggets that invited his

mouth. “Easing your tension,” he announced in a matter of fact tone,

despite the heat flooding his loins and engorging his sex. He came

down over her, his hips lodging between her thighs, his upper body

weight braced by his arms. “As sexist as that probably sounds.”

She squirmed, trying to free herself, and a sound of fury burst out

of her when she failed to budge him.

Spence abruptly says their children should have names. She asks

what children; they are not getting married. He declares his love.

She asks if he is sure. He’s “‘never been more sure of anything in

my life.’” He asks if she will make babies and grow old with him.

“‘Yes, Yes, Yes!’” Then they make love “as their bodies, hearts and

souls mated forever.”141

This is very rough sex, in which consent comes only after the

man has forcefully and matter-of-factly stripped off the woman’s

clothes and placed his nude and aroused body between her legs. It

comes as the high point in a fantasy aimed at women.

There have been many academic studies of sexual fantasies.

One of the most interesting has found that pornographic films can

be classified by theme. Of the nine themes reported by psychologist

Roy Baumeister, the one that was by far the most sexually arousing

for women

involved a woman who was initially reluctant to have sex but changed

her mind during the scene and became an active willing participant

in sexual activity.142 [This study and another] suggest that the woman’s

transition from no to yes, as an idea, increases sexual excitement.

A review of the literature on sexual fantasies found that fantasies

of being overpowered and forced to have sex were far more common

among women than men. In some studies, over half the female sam-

ple reported fantasies of being overpowered, and other research found

a third of women endorsing such specific fantasies as being a slave

who must obey a man’s every wish. When women are given lists of

sexual fantasies to choose among, that of being forced sexually is

sometimes the first or second most frequently chosen one.

And the ubiquitous rape fantasies: http://www.psychologytoday.com/blog/all-about-sex/201001/womens-rape-fantasies-how-common-what-do-they-mean

To proliferate their genes, our male ancestors either mated with

many women or promoted their offspring’s survival by supporting

and defending the mother and children. In a subculture where it is

possible to take either the quantity or the quality approach to sir-

ing the next generation, McSeed, with less of what social scientists

call “embodied capital” than more mainstream males, is better able

to succeed with the quantity approach.60 A white version of McSeed

was more recently in the news when the Wisconsin Supreme Court

affirmed a judgment forbidding a man named David Oakley from

having any more children until he supported those he already had.

Oakley, an unemployed factory worker, had nine children by four

different women.

that doesnt sound legal… where is the eugenics police?

besides, quality vs. quantity, see: https://en.wikipedia.org/wiki/R/K_selection_theory

besides, the roles that fathers can provide: resources and protection, we now have the state to be and the police. to be sure, fathers are still those paying for the state and hence the police, but they arent the immediate helper, making them seem less important.

In addition, one letter writer had a question about how to greet

a guy she had hooked up with who never called again, and another

asked whether the guy she slept with on the first date will think she

is a total slut. The “advice guy” responded that it depends on the

guy. A poll in another issue, however, found that 76 percent of male

respondents said they would not date again any girl they slept with

on the first date.

No source given. Really? why does it matter?

Men want more space than women do. In the workplace, men

have a much stronger desire than women for jobs with no close

supervision. Studies show that women like to be alone within the

confines of a bedroom or an office, whereas men are more likely to

need real isolation—a long drive or a trip to the mountains. Think

also of those frequently solitary and overwhelmingly male pastimes,

hunting and fishing. No matter how good their relationships, men

are far more likely than women to report that they need free time

to relax and pursue hobbies away from their mates.119

Boys do travel in large groups, bonded by a mutual interest in

the same activities; but they are relatively more attached to things,

less to people. From childhood, girls but not boys focus on close

relationships and, especially, a best friend.120 When female college

students tell stories about themselves, they speak of friends and com-

munity; they are often giving or receiving advice, and if they act

alone, something bad happens. Men’s stories are very frequently

about acting alone in contests, and they have happy outcomes.121

There is an okcupid question on this one can data mine:

How important is it to you to have your own unique “thing” (like a weekly Girls’ Night Out or Guys’ Movie Night) that you don’t share with your partner(s)?

Very – I need some ME time to be happy

Sort of – I need friends outside of my partner

Not much – I like sharing stuff with my partner

I’d prefer not to have exclusive things

Moreover, it is a massive risk to rely on modern medicine to

help reset the biological clock and make late childbirth safer. Recent

studies have revealed increased rates of major birth defects in infants

born through intracytoplasmic sperm injection and in vitro fertil-

ization over those conceived naturally. Even after controlling for the

age of the mother and other factors, a child conceived by either IVF

or ICSI is still more than twice as likely to be diagnosed with a major

birth defect than is a naturally conceived child.135

probably due to insufficient embryo selection: https://en.wikipedia.org/wiki/Embryo_quality

Women in their late twenties are, with reason, much more pes-

simistic today about ever marrying.139 Studies show that “the older

she gets, the harder it is for a college-educated woman to find a hus-

band.” College-educated women “tend to seek husbands who are

slightly older and have even higher levels of education and achieve-

ment than they do,”140 but the number of men in this already lim-

ited pool declines as women age. So it is not surprising that 63 percent

of women hope to meet their future husband in college. They will

never again be surrounded by so many eligible men who share their

interests and aspirations.

One wonders about the effects of the fact that there are now about 2 women per 1 man with a university degree. If womens hypergamy leads them to select blindly for degrees, there will be a lack of such men. Uh oh!

What does one say to a boy who continually badgers a girl for

oral sex? Or who sticks his crotch in the girl’s face? The answer is

that we can’t say much if we assume that there are no differences

between males and females. We often can get young people to be

more considerate by saying, “How would you feel if someone did

that to you?” That might work if a boy took a girl’s book bag. If

we say, “How would you feel if she did that to you” about the crotch-

in-the-face stunt, the boy is likely to say, “That would be great.”

Most boys don’t find this sort of behavior degrading or obnox-

ious. Why should they believe that girls do? If sex is recreational,

why is it degrading?

Another failing of the golden rule. https://en.wikipedia.org/wiki/Golden_Rule

the generalized failure condition for that is when people do not share interests or desires. if one tries to fix it one gets: act so that ur actions is what the other desires… which is just preference utilitarianism on a local level. ;)

Starting education early might be expected to improve the

school performance of inner-city children; and this does hold true

for girls. Those who went through Head Start are only one-third as

likely as girls of similar socioeconomic backgrounds to drop out of

high school years later. But for boys, Head Start seems to have no

effect on high school completion rates.104

cite goes to: Mathews and Strauss, 2000.

Mathews, Jay, and Valerie Strauss. 2000. Head Start Works for Girls.

Washington Post, 10 October.

meh!

I re-read Murrays description of Head Start studies.

http://www.aei.org/article/education/the-shaky-science-behind-obamas-universal-pre-k/

he writes

This brings us to the third-grade follow-up of the national impact assessment of Head Start, submitted to the government in October and released to the public late last year. Head Start has been operating since the 1960s. After decades of evaluations that mostly showed no effects, Congress decided in 1998 to mandate a large-scale, rigorous, independent evaluation of Head Start’s impact, including randomized assignment, representative samplings of programs and a comprehensive set of outcomes observed over time.

Of the 47 outcome measures reported separately for the 3- year-old and 4-year-old cohorts that were selected for the treatment group, 94 separate results in all, only six of them showed a statistically significant difference between the treatment and control group at the .05 level of probability — just a little more than the number you would expect to occur by chance. The evaluators, recognizing this, applied a statistical test that guards against such “false discoveries.” Out of the 94 measures, just two survived that test, one positive and one negative.

The executive summary is here:

http://www.acf.hhs.gov/programs/opre/resource/third-grade-follow-up-to-the-head-start-impact-study-final-report-executive

In summary, there were initial positive impacts from having access to Head Start, but

by the end of 3rd grade there were very few impacts found for either cohort in any of the four

domains of cognitive, social-emotional, health and parenting practices. The few impacts that

were found did not show a clear pattern of favorable or unfavorable impacts for children.

Head start does NOT WORK.

But the progress that Senator Kennedy wants will come at the

expense of lost opportunities for still more male athletes. From 1985

to 1997, over 21,000 collegiate spots for male athletes disappeared.

Over 359 teams for men have disappeared just since 1992.8

Christine Stolba of the Independent Women’s Forum commented to the

Title IX commission that “Between 1993 and 1999 alone 53 men’s

golf teams, 39 men’s track teams, 43 wrestling teams, and 16 base-

ball teams have been eliminated. The University of Miami’s diving

team, which has produced 15 Olympic athletes, is gone.”9

I didnt know anyone was foolish enuf to have affirmative action for sports…

But the Office of Civil Rights in the Department of Education

rules that cheerleading and competitive dance are not sports, and

that participants do not count for Title IX compliance purposes.

The principal problem seems to be that cheerleaders and dance teams

usually perform to raise spirit at contests played by other, usually

male, athletes.92 As one ex-cheerleader told me, cheerleading has a

selfless quality—it’s getting people to yell for other people.

Apparently it doesn’t matter if these people compete as well

as cheer for others. The Office of Civil Rights deems that at least

half their appearances must be in a competitive setting, or their activ-

ity is not a sport. In response, the University of Maryland recently

divided its cheerleading team into a “spirit squad” and a competi-

tive squad. The latter group will perform only at competitions and

will be eligible for scholarship money, a move “designed to keep

Maryland in compliance with Title IX while returning some schol-

arships to the school’s eight underfunded men’s programs.”

Senior team member Erin Valenti opted to stay with the spirit

squad, which must fundraise to cover its costs. “They’re splitting

us only so they can convince whoever the head of Title IX is that

cheerleading can be considered a sport,” she said. “To make it a

sport, you’re taking out the whole reason to do cheering to begin

with.” That is, the cheering part.93

The Women’s Sports Foundation’s Web page contains a posi-

tion statement supporting the current policies that deny sports sta-

tus to cheerleaders who compete less than they cheer for others.94

But the Web page also has a “Women’s Sports on TV” section that

includes listings for yoga and aerobics shows.95 If yoga and aero-

bics are sports, why aren’t cheerleading and dance?

I rather universities did not have these sports stuff. Its a US thing, or at least DA universities do not do this. They do something else tho, have science show competitions.

there is a european page about it here: http://wiki.europhysicsfun.org/

Not only do these feminists want to limit women’s choices, but

NOW also wants to withhold information that might lead women

to make the “wrong” choices. I noted earlier that many highly edu-

cated women greatly overestimate their chances of getting pregnant

after age forty. In the summer of 2002, the American Society for

Reproductive Medicine wanted to place public service ads in shop-

ping malls and movie theaters that could have helped correct this

misinformation. The ads were designed to enable women to make

reproductive choices based on the facts. In particular, they wanted

to tell women how they could prevent infertility.

The opposition of groups such as NOW aborted the whole

program. The ad that particularly angered NOW contained the mes-

sage: “Advancing Age Decreases Your Ability to Have Children.”

NOW accused the doctors of using “scare tactics.” They further

argued that “the ads sent a negative message to women who might

want to delay or skip childbearing in favor of career pursuits.”139

Some sleep scientists believe that the mothers’ breathing and

heartbeat would help prevent sudden infant death syndrome (SIDS)

if Western mothers slept with their children. This view is controver-

sial with some U.S. doctors who emphasize the instances of adults

inadvertently suffocating babies who share their bed.196 Nonethe-

less, the international comparisons are striking. The U.S. has far and

away the highest rate of SIDS in the world (2 per 1,000)—ten times

higher than Japan and one hundred times higher than Hong Kong,

both countries where mothers routinely sleep with their children. In

most of the world, parents sleep with their young children, and the

lowest incidences of SIDS are in societies with widespread co-sleeping.

Sounds too easy to be true. According to Wiki, it is: https://en.wikipedia.org/wiki/Sudden_infant_death_syndrome

I wrote Meg and asked if she did not think that people have a

tendency to say that things—like marriage—are not all that impor-

tant to them if they think that there is a decent chance they won’t

happen. Psychologically, it’s tough to get through days if things you

desperately want aren’t happening; it seems logical to downplay

their importance. So perhaps it can be tough for women to be hon-

est with themselves about their own desires.

She replied in the affirmative:

I’d say your point about downplaying goals that seem out of reach

is quite valid. The problem is that it’s self-perpetuating; for societal

reasons marriage and family become difficult to obtain, thus women

deny that they want these things, thus they become even more diffi-

cult to obtain because they’ve been deprioritized.

See: https://en.wikipedia.org/wiki/The_Fox_and_the_Grapes

They do not generally understand female-style emotional support.

They are used to helping a pal by downplaying his troubles or giv-

ing advice, not by sympathetically hearing him out. In one study,

98 percent of wives reported that they wanted their husbands to

talk more about their thoughts and feelings.17 For men, problems

call for advice or action, not talk. When told he should show his

wife more affection, one man went home and washed her car.18

Very common problem in M-F relationships, i think.

August 30, 2013

Women in prisons in percent

Filed under: Science — Tags: , — Emil O. W. Kirkegaard @ 14:06

I stumbled across some Men Right’s Activist websites, which i had not payed particularly attention to before, and found something that sounded dubious:

  • There are roughly 5100 men in Swedish prisons and almost 300 women – which is the most disproportionate inmates number by gender in Europe and an obvious proof of leniency propensity on the behalf of the prosecutors and judges when it comes to female criminals;

By law, Swedish men are 2nd class citizens

So naturally i tried to verify that. I found some data and … it was wrong.

http://www.prisonstudies.org/info/worldbrief/wpb_stats.php?area=europe&category=wb_female

Including all the shit countries like Bosnia does not put Sweden on the bottom i.e. with the “most disproportionate inmates number by gender in Europe” as claimed. Even excluding shit countries (anything not northern european minus Ireland) does not help either. France comes at the bottom with 3.3% women. Danmark 3.9%, Norge 5.3%, Sverige 5.8%, Finland 6.7%. Sweden actually comes somewhat near the top, meaning that they are less disproportionate than the other euro countries.

So, either this was an odd case, or MRA’s are quite possibly just as bad as feminists at making shit up / uncritically accepting dubious sounding numbers. Who knows.

June 21, 2013

Paper: Gendered Shopping: A Seven Country Comparison (Ellis et al)

Filed under: Evolutionary Psychology — Tags: — Emil O. W. Kirkegaard @ 01:23

Gendered Shopping A Seven Country Comparison

Abstract

Studies in Western countries have revealed that women spend more time shopping than do men with the exception of online shopping. To extend this finding to non-Western populations, the present study used identical methods of observing visitors to indoor shopping malls in seven different countries. Three of the countries were Western (Canada, Spain, and the United States) and four were non-Western (China, Laos, Malaysia, and Turkey). In all seven countries, the proportion of women significantly exceeded the proportion of men. Among children and adolescents, female also outnumbered their male cohorts in most of the seven countries, although the differences were not always statistically significant. Theoretical explanations for these findings are explored. Overall, we propose that the most credible explanation involves a combination of social, evolutionary, and neurohormonal variables. Key Words: Sex differences; Shopping; Cross-cultural (Canada, China, Laos, Malaysia, Spain, Turkey, United States).

Furthermore, women report enjoying shopping more than do men (Alreck & Settle, 2002; Bellenger and Korgaonkar, 1980; Rook & Hoch, 1985; Seock & Bailey, 2008). A study by Swaminathan et al. (1999) indicated that men and women have different “orientations” to shopping. Basically, men are more oriented toward shopping if and where it is most convenient and least time-consuming; whereas women seem to savor prolonged shopping experiences, especially when they can share the experiences with others (Rook & Hoch, 1985).

The data just screans human nature, not social roles.

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