Download full-text PDF

An S Factor Analysis on the Provinces of Vietnam: Relationships with Cognitive Ability, Ethnicity, and Latitude

Article (PDF Available) inThe mankind quarterly 58(4) · June 2018with255 Reads
Emil O. W. Kirkegaard at Ulster Institute for Social Research
  • 18.13
  • Ulster Institute for Social Research
Bryan J Pesta at Cleveland State University
  • 24.65
  • Cleveland State University
Abstract
We compiled cognitive, ethnic, and socioeconomic data for the 63 provinces of Vietnam. The cognitive data came from math and reading achievement tests administered to 70,000 fifth-graders in 2001 (World Bank, 2004). Ethnic and socioeconomic data were coded from various official sources (e.g., The General Statistics Office of Vietnam). Analysis of the socioeconomic data revealed a general factor (S) that was robust to variations in extraction method and controls. The average cognitive ability of the provinces correlated .47 with the S factor. The strongest predictor of S, however, was ethnicity. Specifically, the percent of Vietnamese (Kinh) within each province correlated .74 with S. Moreover, this effect was not mediated by cognitive ability. The lack of mediation is inconsistent with results from earlier studies that examined relations between ethnicity, cognitive ability, and socioeconomic outcomes (see, e.g., Fuerst & Kirkegaard, 2016). Also inconsistent with prior studies, although latitude correlated positively with cognitive ability, it did so inversely with the S factor. We discuss several potential hypotheses for why these discrepant effects occurred.
Figures
Figure 1. S loadings across four method variations. 
Figure 2. Scatterplot of cognitive ability (CA) and general socioeconomic factor (S). 
Full-text
Content uploaded by Emil O. W. Kirkegaard
Author content
KirkegaardPestaMQVietnam.pdf
1 B
Sorry, there is no online preview for this file type.
Project
A very large dataset (N=68,371, 2,620 variables) from the dating site OKCupid is presented and made publicly available for use by others. This project concerns the original data release, any follo…" [more]
Project
Which stereotypes are accurate and which are not? What explains the variation in accuracy between persons? Why are stereotypes more accurate for some groups than others?
Article
January 2015 · The Winnower
    Two methods are presented that allow for identification of mixed cases in the extraction of general factors. Simulated data is used to illustrate them.
    Article
    May 2017
      The relationships between national IQs, Muslim% in origin countries and estimates of net fiscal contributions to public finances in Denmark (n=32) and Finland (n=11) were examined. The analyses showed that the fiscal estimates were near-perfectly correlated between countries (r = .89 [.56 to .98], n=9), and were well-predicted by national IQs (r’s .89 [.49 to .96] and .69 [.45 to .84]), and... [Show full abstract]
      Article
      January 2017 · The mankind quarterly
        Employment rates for 11 country of origin groups living in the three Scandinavian countries are presented. Analysis of variance showed that differences in employment rates are highly predictable (adjusted multiple R = .93). This predictability was mostly due to origin countries (eta = .89), not sex (eta = .25) and host country (eta = .20). Furthermore, national IQs of the origin countries... [Show full abstract]
        Discover more