Bibliographic record
Abstract
It is commonly hypothesized that education promotes more “enlightened” beliefs about racial inequality, and many prior studies document that white Americans with higher levels of education are more likely to agree with structural rather than individualist explanations for black disadvantages. Nevertheless, an alternative perspective contends that the ostensibly liberalizing effects of education are highly superficial, while yet another perspective cautions that any association observed between education and racial attitudes may be due to unobserved confounding. This study evaluates these perspectives by estimating the effects of education on beliefs about racial inequality from a set of cross-sectional, sibling, and panel models. Consistent with prior research, results from cross-sectional models fit to the General Social Survey (GSS) suggest that education promotes a genuine belief in structural over individualist explanations for racial inequality. However, results from sibling and individual fixed-effects models fit, respectively, to the 1994 Study of American Families and to the 2006–2010 GSS three-wave panels suggest that these effects may be superficial and are likely inflated by unobserved confounding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".