Social movements, knowledge and public policy: the case of autism activism in Canada and the US
Bibliographic record
Abstract
This paper explores the role of social movements in the policy process and, in particular, the ways in which movements interact with, access, and deploy expert knowledge. In the technocratic model, citizens are conceptualized as undifferentiated, rather than considered in terms of distinctive identities or interests. Their inclusion in policy-making is viewed as a technical problem to be ‘solved’ through forms of citizen engagement, rather than viewing citizens as active agents in the mobilization of distinctive knowledges. Citizens, we argue, are more than the undifferentiated lump that appears in the technocratic model under the guise of citizen engagement. Drawing on a case study of autism activism in Canada and the US, we demonstrate the range of ways in which civil society actors both deploy and contest expert knowledge in the policy process, and discuss the implications for how we conceptualize knowledge mobilization in policy processes.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.075 | 0.035 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".