Towards a policy social psychology: Teacher engagement with policy enactment and the core concept of Affective Disruption
Bibliographic record
Abstract
The article uncovers the complex process of educational policy enactment and the impact this process has on teachers as policy actors as they undertake the task of introducing a new mathematics curriculum in a Canadian secondary school. The three year study based on in‐depth qualitative interviews adopts a classic grounded theory approach of concurrent iterative cycles of data collection, conceptual categorisation and analytical abstraction, to identify six emergent concepts indicative of policy actor engagement with the policy process: (1) Professional and Emotional Investment; (2) Decisional Legitimacy; (3) Hierarchical Trust; (4) System Integrity and Viability; (5) De‐professionalisation; and (6) Identity Safeguarding. Further, and significantly, the grounded theory analysis identifies the core concept of Affective Disruption, conceived as an interruption to an individual's emotional equilibrium resulting from interference to their cognitive sense‐making in relation to policy. It is proposed these six emergent concepts and Affective Disruption as a core concept are precipitated within policy actors in response to the tensions created by the process of policy enactment; the research findings moving towards what might be tentatively termed a policy social psychology.
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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 | 0.023 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.086 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".