Meaningful Measurement of Sustainable Development or Gaming the System? Patterns in Submission to Times Higher Education's Impact Ranking
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
ABSTRACT This research takes a quantitative approach to investigating patterns in submissions to the Times Higher Education's sustainability‐focused Impact Ranking. Testing hypotheses developed from the quantification, rankings, and disclosures literatures, this research provides a first‐of‐its‐kind longitudinal exploration into the Impact Rankings to understand the shape that submissions take along two categories: universities' responses to previous submissions and universities' own characteristics. The study finds that the universities that submit the most sustainable development goals tend to have larger student populations and score higher. It also finds that universities do not seem to target specific high‐scoring goals but rather resubmit the same goals and increase the number of submissions per year. This research will be of interest to researchers in the areas of disclosures, rankings, and higher education, and will also be of interest to practitioners currently working in university offices of sustainability.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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