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Record W2077198820 · doi:10.1080/13540602.2011.580527

Teacher-centered professionalism: a feminist perspective on supported access to digital knowledge

2011· article· en· W2077198820 on OpenAlexaboutno aff
Sarah Twomey

Bibliographic record

VenueTeachers and Teaching · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningThe InternetSociologyPerspective (graphical)PedagogyValue (mathematics)Reading (process)PsychologyPolitical scienceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This qualitative study creates a case for teacher learning through increased access to digital knowledge and information made available through the Internet. I ask how reading environments, supported through online access to scholarly texts, might create intellectual engagement and transformative possibilities for teachers within their professional learning communities. This study is based on the experiences of six female teachers’ participation in a research project in a large urban center in Western Canada. Through individual and group interview data, I present three examples of how the teachers engaged in a discourse of social justice. This paper demonstrates the value of providing teachers with digital access to public knowledge through the Internet as a new and distinctive approach to teacher learning that can deepen understanding of the profession within a collective association of learning.

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)0.008
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.041
Scholarly communication0.0090.007
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.139
GPT teacher head0.355
Teacher spread0.216 · 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.

Study designQualitative
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

Citations1
Published2011
Admission routes1
Has abstractyes

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