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[ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial

#41
Hello Meng Hu,

Thanks for your review.

I can fix the missing bracket and add the following link as a footnote. It offers a detailed description of data, people, and things:

http://www.occupationalinfo.org/appendxb_1.html


ETA: What's next?

(2016-Jul-07, 01:09:07)Meng Hu Wrote: I like the article. That there is a prediction that the % of racial composition changes as IQ job (or complexity) increases is supportive of Spearman's hypothesis, also shows (or rather, suggests) that within-correlation of IQ*job complexity may also extend to between-group context (as Gottfredson compiled lot of research showing that this correlation holds within groups, white groups) as the hypothesis expected.

I have no problem with the consistency/stability of the correlations, and their magnitude and signs indeed are supportive of the studied hypothesis.

I would appreciate if you can describe a little bit more the variables of worker activity, namely, data, people, and things, because it may not be very clear to everyone (e.g., I have only a rough idea).

Quote:They score six (“speaking-signaling”) on people, and two (“operating-controlling) on things.

You forgot a bracket.

(2016-May-30, 21:37:35)Chuck Wrote: I was suggesting that you might qualify your statement. For example, for precision, I might say: Spearman's hypothesis would predict that group differences are larger on more g-loaded tests, assuming no countervailing psychometric bias. Likewise: Spearman's hypothesis would predict that employment differences are larger for more g-loaded fields, assuming no countervailing societal bias e.g., affirmative action or defacto quotas. If you think that the qualification is obvious, don't bother.


It has little to do with the core of this study but I don't remember that Jensen said anything like this. In fact, I think Jensen's reasoning is in accordance with Dolan, in that that if there is bias, any finding in support of SH would be unreliable. They however don't disagree about the method to detect bias (but that, you and I, we already know very well).

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#42
"Spearman’s hypothesis equates race differences with g differences, and predicts that the former will covary with how well mental tests measure the latter"

This is too strongly worded. Firstly, Spearman's hypothesis originally concerned only black-white differences even if it has later been applied (with less success) to other comparisons. Secondly, "equating" suggests a strong version of the hypothesis, which everybody agrees is unsupported. The hypothesis in its weak form suggests only that race and g differences are strongly collinear.

"We also found a very large correlation (.86) between job IQ and complexity"

I would clarify that this is an ecological correlation.

As to the discussion about whether the study really tests SH, I'd say it's an indirect test of SH that depends on the correctness of the theoretical assumptions you make. Specifically, you assume that job g can be equated with job IQ and that job complexity ratings can be equated with g loadings. Of these analyses the one with job IQ is somewhat circular (IQ varies between groups, so higher-IQ groups are better represented in higher-IQ occupations). The job complexity analysis is more interesting as it is, at least in principle, independent from job IQ data.

So, I think you can describe the study as a test of SH as long as you stress that you use theoretically plausible proxy variables for measures of g saturation.

Can you add a scatterplot (or some other kind of graph) with racial proportions in jobs on one axis and job complexity on the other (with the complexity/data variable reverse-scored)? Raw racial proportions may not be the perfect variable for your analysis, but a graph could make the relationships that exist more transparent.
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#43
Bryan Pesta, I am OK with the proposed changes. I'm giving you my approval. Although I concur with others that an analysis of the hispanic group can be done, I see no real problem with the analysis as shown.

Although it's not a condition, I would like that you add a third table for the regression analysis. I think the regression analysis is at least or more important than the correlation analysis, especially concerning the prediction about %asians. Without displaying results on a table, it may give the impression that it's of lesser importance while it's not.

Quote:It appears that values on People suppress the true correlation between Job IQ and percent Asian.

If you want, say explicitly that People variable act as a suppressor effect, as far as job IQ is concerned.

See below:
http://ericae.net/ft/tamu/supres.htm

Quote:Conger (1974) provided another definition of suppressor variables as, "...a variable which increases the predictive validity of another variable (or set of variables) by its inclusion in a regression equation" (pp. 36-37).
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#44
Hello,

I think I've addressed all concerns-- except one-- since version 2, dated 6/16. Please let me know if I missed anything.

1. De-hark. Done.
2. Change use of the word "correlation" to "relationship" regarding the true results for percent Asian.
3. I've included a footnote that links a detailed explanation of the DOT elements.
4. I fixed the missing bracket / quotation in the intro.
5. I toned down the definition (e.g., dropped "equates") of SH in the abstract.
6. I've mentioned the correlations are aggregate / ecological in the discussion.
7. I mentioned that IQ scores are only proxies for g in the limitations paragraph.
8. I took care of the sentence on supression and stated that this is a suppression effect.
9. I created Table 3, which includes Emil's suggested regressions.

I did not include a graph or figure showing how complexity and ethnicity relate. I spent some time on this with SPSS and the graphs looked stupid / non-informative. I think this is because I lack skill at making pretty graphs, but also because "Data" is binned into just seven possible values (0-6) on one axis, and on the other axis, things get smooshed, as % White hovers in the 70s, and the other race variables hover in the 10s.

Let me know if I missed something, and thanks to all for your input.

Bryan
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#45
Personally, I have nothing to add to what I already said before. Just waiting to have a look at your final version.
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#46
Can you post the newest version of the article? I accept it for publication, but I could take a look at the updated version.

I think a stacked bar chart with mean racial proportions on the y axis and job complexity on the x axis would work. Something like this (the other14 variable is 100-the other racial proportions, jobcomplexity is the data variable reverse coded):

[Image: jobcomplexity.png]

Here's the SPSS code for that:

COMPUTE jobcomplexity=6-data.
EXECUTE.
COMPUTE other14=100-white14-black14-asian14.
EXECUTE.
GRAPH
/BAR(STACK)=MEAN(white14) MEAN(black14) MEAN(asian14) MEAN(other14) BY data
/MISSING=LISTWISE.
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#47
Wow, I could of swore I included the paper as an attachment. Here it is!

I'm ok with adding that figure, if you're ok with me stealing it!

Bryan

(2016-Jul-10, 17:23:57)Dalliard Wrote: Can you post the newest version of the article? I accept it for publication, but I could take a look at the updated version.

I think a stacked bar chart with mean racial proportions on the y axis and job complexity on the x axis would work. Something like this (the other14 variable is 100-the other racial proportions, jobcomplexity is the data variable reverse coded):

[Image: jobcomplexity.png]

Here's the SPSS code for that:

COMPUTE jobcomplexity=6-data.
EXECUTE.
COMPUTE other14=100-white14-black14-asian14.
EXECUTE.
GRAPH
/BAR(STACK)=MEAN(white14) MEAN(black14) MEAN(asian14) MEAN(other14) BY data
/MISSING=LISTWISE.



Attached Files
.docx   Spearman_odp3.docx (Size: 33.95 KB / Downloads: 408)
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#48
It is easier to keep track of files if they are put on OSF instead of as attachments here. Recall that I made a repository for the paper here: https://osf.io/pxmjc/

I will of course transfer the control of this repository to the authors if they make a user on the website. In the meanwhile, I have uploaded the (3rd) version of the paper posted above.
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#49
OK, I approve publication. Go ahead and use the figure, although I'd suggest you divide the y axis values by 100 and use more descriptive labels.
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#50
I will be attending the ISIR conference in Saint Petersburg and may not be able to publish this paper to the website until I get.

http://www.isironline.org/2016-st-peters...uly-15-17/
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