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Record W2143469417 · doi:10.7202/1014863ar

Action Research Built on Uncertain Foundations: The internship and action-research in a graduate teaching degree

2013· article· en· W2143469417 on OpenAlexvenueno aff
Tony Loughland, Margo Bowen

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipRationalityAction (physics)General partnershipPedagogyGraduate educationAction researchSociologyTeacher educationMathematics educationMedical educationPsychologyMedicineEpistemologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

This paper analyses action research’s uncertain foundations in graduate teaching degrees. This analysis focuses on one Master of Teaching program in Australia, and is conducted by the program coordinator in partnership with a recent graduate of the program. Uncertainty is traced to the structural incoherence of the program that is created by the influence of disparate philosophies of teacher education. The philosophy and practice of the program is informed by both the scholar teacher and reflective practitioner models of teacher education. It is argued that these models are incommensurable and lead to a poor use of action research during the internship of the program. The action research would be more authentic if a phronetic model of teacher education underpinned the entire program rather than just the final internship. This phronetic model will remain an ideal because of the prevailing hegemony of neo-liberalism that supports a means-rationality associated with performing to the graduate standards rather than a values-rationality associated with developing a lifelong habit of phronetic practice.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
grokno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualmedium
opusMetaresearch
Domain: Methods · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.078
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.088
Scholarly communication0.0160.015
Open science0.0020.017
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.935
GPT teacher head0.665
Teacher spread0.271 · 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

Labeled directly by 3 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Theoretical or conceptual
DomainMethods
GenreMethods · Commentary

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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

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