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
An overlooked aspect of the diffusion of a practice in a population is the emergence of a de facto classificatory schema, distinguishing between actors that adopt a practice and those that do not. To investigate diffusion as classification, I develop a simulation model that highlights the conditions under which limited diffusion of practices leads to the emergence and entrenchment of classificatory schemas. The model depicts classification as a systemic phenomenon resulting from the interplay of actor-level micromotives and field-level macrobehaviors that jointly drive diffusion. Whereas extant theory on the origin of classificatory schemas emphasizes the role of agency, results from the model suggest that classificatory schemas can emerge somewhat unintentionally as practices diffuse. Moreover, by conceptualizing diffusion as classification, I suggest a means for disentangling the closely related and often conflated concepts of diffusion and institutionalization.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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