Brain Politics: Aspects of Administration in the Comparative Issue Definition of Autism‐Related Policy
Bibliographic record
Abstract
The construction of public problems has a lasting influence on implementation in a given policy subsystem. National and sociopolitical contexts influence issue definition differently across nations. However, the degree to which nation‐specific issue definition takes place has been insufficiently explored. In recent years, the growing incidence of autism has led to a quest for causal factors. One hypothesis posits that the use of mercury in vaccines may be a culprit. This paper examines the definition of the mercury and autism issue in Australia, Canada, the United Kingdom, and the United States. Insights into the comparative elements of issue definition are suggested by the case. These insights are of particular importance to administrators, as agencies are deeply involved as objects and actors in the process of issue definition and are often responsible for implementing new and redefined policies.
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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 | 0.065 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.011 | 0.045 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".