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Educational Policy and Assessmentin Music

2019· reference-entry· en· W2952959787 on OpenAlexaff
Patrick Schmidt

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsWestern University
Fundersnot available
KeywordsFraming (construction)PoliticsPublic policyPolicy analysisWork (physics)PerceptionEducation policyPolitical scienceSociologyAction (physics)Value (mathematics)Public relationsPublic administrationEngineering ethicsEpistemologyHigher educationLawEngineeringComputer science

Abstract

fetched live from OpenAlex

This chapter provides an understanding of policy as a contested educational terrain where complex realities, the challenge of diverse interests and constituencies, and distinct perceptions of value, all contribute to decision-making processes that are anything but objective. The chapter discusses policy as a field of thought and action and highlights the deeply political structure of policy work. It provides an account for the challenges of ethics within policy and decision-making. The chapter places assessment as a significant area in policy exploration and an essential contributor to policy work as an aspect of public spheres of influence. The author also submits that educators should approximate themselves to policy and policy thinking (conceptually and strategically) as their voice and contribution is a needed aspect of the process. The author suggests that the notion of framing disposition be advanced as a tool for approaching policy work within education and music education.

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0080.012
Scholarly communication0.0230.014
Open science0.0020.009
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0270.003

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.

Opus teacher head0.089
GPT teacher head0.299
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations12
Published2019
Admission routes1
Has abstractyes

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