Qualified Equal Opportunity and Conditional Mobility: The Educational Attainment Gender Gap in Canada
Bibliographic record
Abstract
Mount Allison University for their helpful comments and suggestions. Generational mobility policies which follow a Pure Equal Opportunity (EO) social justice imperative seek to reduce the connection between parent and child outcomes. Here it is demonstrated that, in the face of limited ability to raise average offspring ability, singular pursuit of this imperative inevitably involves breaking the connections between high type parents and their children as well as those between low type parents and their children. This does not accord with observed practice wherein EO policies (e.g. Head Start, No Child Left Behind) appear to focus on the latter rather than the former. It is conjectured that policy makers are responding to other imperatives which can be summarized as to not make the inheriting generation of any parental class worse off by the mobility policy. Indeed when this secondary imperative is added to the policy maker’s objective function, together with some capacity for improving mean child outcomes, a Qualified Equal Opportunity (QEO) policy emerges, one more akin to observed practice. The consequences of QEO policies for mobility measurement
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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".