Bibliographic record
Abstract
Most of the formal studies of cultural policy concentrate on the role of central governments and their approaches to supporting the arts, creative industries and heritage. Less attention has been given to cultural policy at the sub-national level despite the fact that the states in the United States, the provinces in Canada and the states of Australia, for example, all run extensive programs of cultural support. This paper introduces some new thinking about the role and contribution of cultural programs at the sub-national level, illustrating these ideas by reference to the role of the states in the United States. It is based on a pilot project for the Mapping of State Cultural Policy in the United States. This project, which began in late 2001 and will produce its first report in the summer of 2003, draws its inspiration from the Council of Europe’s Program of Reviews of National Cultural Policies and has been funded by The Pew Charitable Trusts.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.018 | 0.025 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".