MétaCan
Menu
Back to cohort
Record W4229997408 · doi:10.1080/02783193.2011.603111

Creative Teachers

2011· article· en· W4229997408 on OpenAlexaff
Gillian Bramwell, Rosemary C. Reilly, Frank R. Lilly, Neomi Kronish, Revathi Chennabathni

Bibliographic record

VenueRoeper Review · 2011
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsToronto Public HealthConcordia UniversityMcGill University
Fundersnot available
KeywordsCreativityPsychologyInterviewPseudonymVariety (cybernetics)PedagogyQualitative researchMathematics educationSocial psychologySociologySocial science

Abstract

fetched live from OpenAlex

Good teaching is creative teaching, yet there is little research focusing on creative teachers themselves. In this article we report a synthesis of 13 qualitative case studies and 2 quantitative studies of teachers who demonstrated everyday or local creativity in their work. Themes and categories were identified through constant comparison and interrelationships among themes were explored. Four themes are described: personal characteristics, community, process, and outcomes. Teachers' creative processes emerged from the interaction between their personal characteristics, including personal intelligences, motivation, values and the communities in which they worked and lived. These processes resulted in a wide variety of outcomes. The findings suggest that cooperation between teachers and administrators is essential for teachers to succeed in creating positive change.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.005

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 head0.160
GPT teacher head0.416
Teacher spread0.256 · 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
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

Citations51
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueRoeper ReviewSame topicCreativity in Education and NeuroscienceFrench-language works237,207