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Revisiting the Storied Landscape of Language Policy Impact Over Time: A Case of Successful Educational Reform

2005· article· en· W2015093250 on OpenAlex
Janna Fox

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

VenueCurriculum Inquiry · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsCarleton University
Fundersnot available
KeywordsHindsight biasMainstreamPerspective (graphical)Education reformScale (ratio)Political scienceSociologyEconomic growthPedagogyPrimary educationGeographyLawPsychologyEconomics

Abstract

fetched live from OpenAlex

The many failures of large‐scale top‐down educational reforms are well documented in the reform literature. These failures are most evident when they are reviewed from the advantageous perspective of hindsight. What are less well documented are the extraordinarily interesting, centrally driven educational changes that have had important and lasting impacts over time, not only because they are rare, but also because they have often occurred outside the mainstream (North American) focus of the reform literature. This article provides a retrospective review of one such educational reform as unique as the tropical island country in which it occurred. Revisiting this storied landscape (Clandinin & Connelly, 1995) provides insight into the process and potential of a systemwide educational reform.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.461
Teacher spread0.429 · 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