URBAN EDUCATION / MARCH 2001James, Haig-Brown / UNIVE SITY-SCHOOL PARTNERSHIP “RETURNING THE DUES” Community and the Personal in a University-School Partnership
Bibliographic record
Abstract
This study uses interviews to explore students ’ perspectives of a university path program, one initiative of a university-school partnership. Responses show that the abstraction of the program lives in concrete and personal dimensions for stu-dents as they move from high school to university in the same neighborhood. Advanced placement work at the university and the secondment of faculty from the school board blur distinctions between school and university. Most striking is the students ’ desire to contribute to the community that has supported them and is most closely associated with their families, the school, and the university that lies, at least geographically, within community bounds. But also I am thankful to be here [in Canada], so I’m paying, well, it’s not really paying back, but I want to return my dues. So if I’m not going into teaching, I’m probably going into some service field.... It’s very silly, but it’s deep-rooted in me that I’m thankful to be here. —Nguyen (interview regarding the Partnership Project, December 8, 1997) I think the two are intertwined for me because in my part-time [work], I’ve always helped at the community center and I’m always
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.003 |
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".