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Record W2535393867 · doi:10.14507/epaa.24.2149

Portrait of a Teach for All (TFA) teacher: Media narratives of the universal TFA teacher in 12 countries

2016· article· en· W2535393867 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducation Policy Analysis Archives · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNarrativeCharacter (mathematics)PortraitOpposition (politics)Character educationSociologyRepresentation (politics)Mass mediaTeacher educationTeacher preparationPedagogyAestheticsPsychologyLiteratureHistoryPolitical scienceArtArt historyLawMathematics

Abstract

fetched live from OpenAlex

This article employs narrative analysis to examine how the media in 12 different countries characterize the Teach for All (TFA) teacher. Examining mass media narratives in these 12 countries illustrates that there are some remarkable commonalities in the narratives and character portraits co-constructed and propagated by the media. At the core of these narratives is the notion of a problem in education. This problem justifies the creation and emergence of a character, commonly constructed in opposition to traditionally certified teachers, who embodies the characteristics and attributes of the contemporary neoliberal subject. This article discusses the implications of this character’s widespread representation; namely, how does the character construction influence the broader public perception about education and how is it contributing to the (re)imagination of the role of the teacher?

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.494
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.354
Teacher spread0.332 · 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