FEATURE ARTICLE Making “The List” Business School Rankings And The Commodification Of Business Research1
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
N HIS New Yorker essay on college admissions practices, Gladwell (2005) reflects on how he chose which post-secondary school to attend. He recalls that: In Ontario, there wasn’t a strict hierarchy of colleges. There were several good ones and several better ones and a number of programs…that were world class. But since all col-leges were part of the same public system and tuition everywhere was the same (about a thousand dollars a year, in those days), and a B average in high school pretty much guar-anteed you a spot in college, there wasn’t a sense that anything great was at stake in the choice of which college we attended. (n.p.) Obviously, higher education has seen many changes in the past twenty years. Not only have universities become known for specific areas of excellence, but business schools in particular have become widely differentiated. The “stakes ” have certainly changed. Perhaps one of the most noticeable changes in recent years has been the appearance of multiple school rankings, generated by popular press periodicals such as MacLean’s magazine in Canada, and US & World News Report in the United States. These publications typically create special issues devoted to assessing various post-secondary institutions according to a wide number of criteria, including innovativeness, reputation, and class sizes. Although many educational programs have been ranked, business school rankings appear to be particularly popular; media rankings of undergra-duate, MBA, EMBA, and executive development programs have been conducted by Business-
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 | 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