Bibliographic record
Abstract
We entered academe at the time the Soviet Union and apartheid collapsed. Just as we were starting our doctorates in organizational analysis at the University of Alberta, these seemingly immutable structures that had occupied such a central cultural and political position since the Second World War (and for our entire lives), simply disappeared. Our seminar discussions, and, perhaps more importantly, endless informal conversations in Java U (our favorite campus coffee shop) and the Power Plant (the graduate student bar), were energized and shaped by these fundamental social changes. We argued for hours about the usefulness of existing theories of society and organization in understanding these events, whether this mattered, and what to do about it. Our entire PhD experience was shaped by the challenge of figuring out what these kinds of events meant for social theory. We were especially moved by the images of citizens with sledgehammers breaking down the Berlin Wall and eventually distilled our concerns into a question: we wanted to know why, if social structures that seemed as enduring as these could be changed by people working together, were purposeful agents so absent from the social theory that we were studying? The world was evidently not just mutable and changing, it was changeable by the purposeful acts of common citizens! This was an exciting idea that we spent many hours discussing, and eventually writing about.
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.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.510 | 0.288 |
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".