Why Policy Issue Networks Matter: The Advanced Technology Program and the Manufacturing Extension Partnership
Bibliographic record
Abstract
Why Policy Issue Networks Matter: The Advanced Technology Program and the Manufacturing Extension Partnership, Paul M. Hallacher, Lanham, Maryland: Rowman & Littlefield Publishers, 2005, pp. ix, 181. The argument that the rigid institutional arrangements of the past, namely subgovernments, have given way to decentralized, more open and informal policy issue networks is increasingly supported by a burgeoning body of case study literature. Paul Hallacher's book is an example of one such study that attempts to go beyond this observation and hypothesize the causal connections between policy subsystem structure and policy outcomes in the area of American cooperative technology policy. The United States provides a suitable environment for examining the hypothetical link between policy subsystem and outcome in this policy area because of the differences in political culture at the federal and state levels with regards to government in assisting industry. These differences have manifested themselves as open conflict between Democrats and Republicans over interventionist policy.
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.026 | 0.039 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.016 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 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".