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Record W2010760687 · doi:10.1080/00220270210151089

The 'good' teacher in a neo-liberal risk society: a Foucaultian analysis of professional growth plans

2003· article· en· W2010760687 on OpenAlexaboutno aff
Tara Fenwick

Bibliographic record

VenueJournal of Curriculum Studies · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthosIndividualismConfession (law)ReflexivitySociologyPedagogyProfessional developmentConstitutionPower (physics)Political scienceLawSocial science

Abstract

fetched live from OpenAlex

This study uses Foucault's concept of pastoral power to explore the role of professional growth plans in the constitution of teachers' knowledge, identities, and practice. It examines the production of particular norms of the 'good' teacher internalized and self-regulated through the technologies of self deployed through such plans. These norms embed values of individualism, technicism, reflexivity and 'enterprising self, supporting a neo-liberal ethos in contemporary risk society. It draws evidence from a qualitative study of teachers and principals in Alberta, Canada, implementing a provincial initiative for mandatory growth plans. Such growth plans normalize the 'fact of growth' and align teacher growth to district interests, naturalize consent to surveillance and confession, encourage teachers to internalize goal-oriented practice, reflectivity and self-regulation, and technicize teacher knowledge.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.011
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.037
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.408
Teacher spread0.342 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations35
Published2003
Admission routes1
Has abstractyes

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