The 10,000 PhDs project at the University of Toronto: Using employment outcome data to inform graduate education
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
The purpose of the 10,000 PhDs Project was to determine the current (2016) employment status of the 10,886 individuals who graduated from the University of Toronto with a PhD in all disciplines from 2000-2015. Using internet searches, we found that about half (51%) of the PhD graduates are employed in the post-secondary education sector, 26% as tenure-track professors, with an additional 3% as adjunct professors and 2% as full-time teaching-stream professors. Over the time-period 2000-2015 there has been a near doubling in PhD graduates with the biggest increase in graduation numbers for the Physical (2.6-fold) and Life Sciences (2.2-fold). Increasingly, these graduates are finding employment in the private and public sectors providing the highly qualified personnel needed to drive an innovation economy.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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