College-to-University Transfer Pathway in Ontario through the Eyes of Black Transfer Students
Bibliographic record
Abstract
College-to-University Transfer Pathway in Ontario through the Eyes of Black Transfer StudentsABSTRACTThis study aims to help college-to-university transfer pathways to achieve their policy objective of functioning as a mechanism of social equity and inclusion by facilitating alternative access to university-based education for students from historically disadvantaged backgrounds. The study identifies a number of institutional and social constructs which weaken the ability of these pathways to act as a meaningful corrective of social disadvantage. The study offers a line of thought about this issue by examining the experiences of Black college-to-university transfer students in a major research university of the Canadian province of Ontario. Using interview data obtained from Black transfer students and administrative staff, the analysis identified four themes: (1) racial essentialist the racism of low expectations; (2) underrepresentation; (3) and other inadequacies associated with the transfer ecosystem such as credit recognition and academic advising. The research underscores the importance of incorporating Black transfer students’ perspectives into the policy and practice of transfer pathways. The study additionally offers recommendations for institutional leaders interested in eliminating barriers which hinder educational pathways from achieving the social equity objectives assumed in policy.Keywords: education pathways; race; social mobility
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.042 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".