Qualified Equal Opportunity and Conditional Mobility: Gender Equity and Educational Attainmant in Canada
Bibliographic record
Abstract
Interest in Economic and Social Mobility is rooted in a societal aspiration for equal opportunity. The aspiration is based upon an Egalitarian Political Philosophy which approves of differential outcomes when they are the consequence of differential effort and disapproves of differential outcomes when they are the consequence of differential circumstance and results in "level playing field" policies. In the absence of any other imperative, such policies would result in increased upward mobility for the poorly endowed and increased downward mobility for the richly endowed. Adding a Utilitarian imperative (the inheriting generation should not be made worse off in a first order dominance sense) to societal objectives results in a "Qualified Equal Opportunity or Conditional Mobility" policy which calls for rethinking the approach to mobility measurement. Techniques for evaluating the impact of such policies (both in terms of generational regressions and transition matrices) are proposed and exemplified in considering the issue of Gender Equity in educational attainment in Canada over the last 20 years. The evidence is that women have more than caught up with men and that, in closing the gap, it is the poorly endowed women who have made the most progress in terms of mobility whilst the mobility of males has remained relatively constant across the endowment spectrum consistent with a Qualified Equal Opportunity program.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".