Cambridge Social Ontology: Clarification, Development and Deployment
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
Social ontology—the study of the nature and basic structure of the social realm—is currently enjoying a period of sustained growth and development, both as a field of study in its own right and as a project concerned with under-labouring for a variety of different social scientific disciplines including economics. One of the most active streams in this area emanates from Cambridge and a group of researchers operating at the interface between social ontology and heterodox economics whose work is sometimes identified as Cambridge Social Ontology. The central figure in this project is Tony Lawson, whose work has provided much of the impetus for Cambridge Social Ontology over the last thirty years. This Special Issue of the Cambridge Journal of Economics is intended to mark the contribution Lawson has made to the study of social ontology and to the application of its results to economics and the social sciences more widely. It does so by presenting a range of new papers whose authors were invited to engage with the work of Lawson and his colleagues in the Cambridge Social Ontology project. The intention was to encourage new work, whether it be critical or constructive in orientation, and thereby hopefully to advance the themes that Lawson has pursued over the course of his career.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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