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Record W2039012803 · doi:10.14507/epaa.v15n1.2007

Hugging the Middle

2007· article· en· W2039012803 on OpenAlexaboutno aff
Larry Cuban

Bibliographic record

VenueEducation Policy Analysis Archives · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityContext (archaeology)Quarter (Canadian coin)Metropolitan areaUnintended consequencesStudent achievementPolitical sciencePedagogyState (computer science)Mathematics educationPublic relationsPsychologySociologyPublic administrationAcademic achievementHistoryLaw

Abstract

fetched live from OpenAlex

In the last quarter-century and especially the last decade, testing and accountability have come to dominate education policy at the state and national levels. The common concern about the effects of such testing is that it reshapes teaching in the classroom. But such claims do not look at the evidence of deeper classroom structures (the mix of teacher-centered and student-centered practices) in historical context. This article extends historical research in How Teachers Taught (Cuban, 1993) to the present in three metropolitan school districts. While testing and accountability have become more obvious concerns of teachers, the hybridized classroom environment documented in How Teachers Taught have become more pervasive. This article documents this continuing ubiquity and addresses the apparent inconsistency between evidence of a hybridized classroom environment and the unintended consequences of testing and accountability.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.021
Scholarly communication0.0120.012
Open science0.0010.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0270.004

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 head0.041
GPT teacher head0.378
Teacher spread0.337 · 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 designObservational
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

Citations50
Published2007
Admission routes1
Has abstractyes

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