Preference for Prestige: Commentary on the Behaviour of Universities and their Benefactors
Bibliographic record
Abstract
This paper examines institutional behaviour, as perceived and described by individuals who have donated large gifts to private non- profit (not-for-profit) corporations especially universities. The study improves the understanding readers may have of the means used by Canadian institutions to initiate relationships with individuals capable of making large gifts, of how these relationships are nurtured, of who in the organization influences decisions about the purposes served by gifts from these donors and of how institutional and/or personal prestige are factors in donor-recipient relationships. More significantly, the study explores the degree to which institutions involve major donors as partners in enhancing an institution's reputation for quality. Data reported here were gathered from interviews with donors to universities, hospitals and arts organizations in Toronto. The responses of donors are reported and some differences identified between donors to universities and donors to either hospitals or arts organizations. With the largest generational transfer of wealth in history starting to occur, the findings may prove useful to universities as they compete for charitable dollars with other nonprofit organizations.
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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 | 0.019 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.020 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".