MétaCan
Menu
Back to cohort
Record W2182949795 · doi:10.36510/learnland.v2i2.291

Commentary: The Politics of Curriculum Creativity

2009· article· en· W2182949795 on OpenAlexvenueno aff
Madeleine R. Grumet

Bibliographic record

VenueLEARNing Landscapes · 2009
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityCurriculumPoliticsSubordination (linguistics)CorporationFoundation (evidence)SociologyPedagogyPolitical scienceEngineering ethicsPublic relationsLawEngineeringPhilosophy

Abstract

fetched live from OpenAlex

As we encourage creativity in curriculum, we often forget that the whole agenda is made up. Creativity is the foundation of all knowledge and all curriculum. In this essay I argue that teachers do not need to be more creative, but do need to participate in the politics that will diminish our subordination. Because the creativity of the corporation and the testing companies has swamped the creativity of the classroom, the current economic crisis may provide opportunities for teachers to reassert the authority of our imaginations.

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)0.009
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.083
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.060
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0100.012
Scholarly communication0.0060.010
Open science0.0080.004
Research integrity0.0830.104
Insufficient payload (model declined to judge)0.0090.007

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 head0.018
GPT teacher head0.332
Teacher spread0.313 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations8
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueLEARNing LandscapesSame topicCreativity in Education and NeuroscienceFrench-language works237,207