Affirmative action and education equity in higher education in the United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In recent years, many of the most contentious debates regarding affirmative action in the United States have taken place on the terrain of universities. Numerous court decisions have examined the extent to which university admissions policies may accord preferences to students from underrepresented and racialized groups. There has been much less litigation in the Canadian context; however, the underlying issue of how to insure equality and inclusion in the face of systemic discrimination is a critical concern. Therefore, the purpose of this thesis is to explore the key legal developments regarding affirmative action initiatives in higher education in Canada and the United States, by highlighting the important differences in the justifications. This thesis will advance and explore two divergent rationales that emerge as salient in affirmative action programs in the United States and Canada. In the American context, diversity is adopted as the main justification for affirmative action programs in universities, as opposed to the Canadian context where it is 'ameliorating the conditions of disadvantaged groups,' that is employed as the key justification for what are called education equity programs. In looking at the experience of each country, this thesis will also examine some of the reasons and ways in which we can understand the different approaches and justifications that have emerged in Canada and the United States in the affirmative action debate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it