Do university rankings matter? A qualitative exploration of institutional selection at three southern Ontario universities
Bibliographic record
Abstract
Concern with university rankings have become widespread throughout post-secondary education (PSE), fuelled in part by administrative concerns that demotions down the rank ladder will produce negative institutional outcomes. There is reason to believe, however, that ranking ‘effects’ may be partially muted in Canadian PSE due to the (1) national system’s flatter hierarchical structure and (2) the generally inconsistent findings produced by domestic research on rankings. Through this study, we provide a qualitative analysis of how rankings shaped the institutional selection processes of 90 undergraduate students across three universities in southern Ontario, Canada. Our data indicate that these students rarely consulted ranking publications, relying instead on reputational information available through their informal networks (e.g. peers, family). We theorise that the unique structural characteristics of Canadian PSE minimise the influence of rankings within this jurisdiction, and discuss the practical implications of this finding for both scholars and administrators.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".