Bibliographic record
Abstract
Currently, there are a number of disciplines in the social sciences where a “public turn” (Nickel 2010, 698) is being advocated. When one calls upon other scholars to ‘go public’ they are usually asking their colleagues to move beyond what is imagined to be their comfort zones, to do what is allegedly unusual, and engage publics beyond their university classrooms and other academic forums to impact social change concerning the substantive topics addressed in their research. These clarion calls are often set against a contextual backdrop where the world is thought to have just recently gone to shit due to populist politics, mass ignorance and lack of exposure to, or adherence to the lessons found within, academic studies. The proposed antidote offered by proponents of public social sciences often comes in the form of cold, hard ‘truths’ that scholars are claimed to be well-positioned to provide, but too often fail to effectively communicate because of the narrow scope of publics they normally engage.
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 | 0.027 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.024 | 0.076 |
| Scholarly communication | 0.030 | 0.037 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.032 | 0.033 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".