Editorial introduction: Assemblage, enactment and agency: educational policy perspectives
Bibliographic record
Abstract
The idea for this special issue emerged after a panel held at the 7 th International Conference on Interpretive Policy Analysis in 2012 in Tilburg, the Netherlands.Our goal for the panel was to bring together recent work around the notions of assemblage, enactment and agency in educational policy analysis, with particular attention to issues of subjectivity, practice, power, and relationality.After the conference, we invited other papers to form a special issue on these topics.The collection of papers in this issue aims to explore the emerging shift in policy research towards analyses embracing the notion of policy enactment, and specifically, theorizations that attend to the … creative processes of interpretation and translation, that is, the recontextualisation -through reading, writing and talking -of the abstractions of policy ideas into contextualised practices.(Braun, Ball, Maguire & Hoskins, 2011, p. 586) These new approaches offer innovative and exciting opportunities for exploring the complexity of policy processes in educational fields.The authors in this issue share an interest in critiquing linear views of policy processes for their limitations in understanding complexity in policy research.Such linear views of policy have a tendency to separate processes of policymaking into discrete categories of design, implementation, and evaluation that privilege the agential actor as instrumental decision maker.The interpretive turn in policy analysis (Yanow, 2000) has been critical of these approaches, arguing that their focus is on policy goals aimed a predefined problems with pre-defined outcomes.As Shore and Wright (2011) argued, instrumentalism still dominates much of the policy analysis research, particularly in the field of educational policy.Within the interpretive turn in policy analysis, the notion of policy enactment not only poses challenges to linear conceptualizations of policy design, implementation and evaluation, but also questions the instrumentalist view of actors, recognizing the role of agency, interpretation, sense-making, translation, embodiment, and meaning throughout the policy process.The scholarship in this area draws upon notions of assemblage (Rizvi & Lingard, 2010); enactment (Ball, Maguire & Braun, 2012), networks (
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.016 | 0.022 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".