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Record W2929561084

Transforming Practice Through Researcher-Practitioner Partnerships

2019· article· en· W2929561084 on OpenAlexaff
Silvia Mazabel, Nikki Yee, Kimberley MacNeil, Donna Kozak, Aloy Anyichie, Ben Dantzer, Shelley Moore, Deborah L. Butler, Nancy E. Perry, Leyton Schnellert

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBridge (graph theory)PedagogyInclusion (mineral)Best practiceMathematics educationSociologyPsychologyPolitical scienceMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Teachers continue to struggle to implement teaching and learning practices that support all students in the classroom, despite significant research in the area. Research-practice partnerships (RPPs) help to bridge the divide between theory and research by facilitating implementation of research-based pedagogy in classrooms, and creating research that is relevant to school contexts. This symposium presents seven examples of how RPPs can be implemented to advance knowledge about pedagogical practices that support inclusion. Findings suggest the dialogue between researchers and practitioners led to the co-construction of knowledge relevant to authentic environments. RPPs facilitated powerful relationships between teachers and researchers that built on the expertise of both, and resulted in intimate connections between research and pedagogy that meaningfully and immediately informed one another.

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)0.132
metaresearch head score (Gemma)0.117
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.697

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1320.117
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0170.053
Scholarly communication0.0330.032
Open science0.0050.037
Research integrity0.0110.015
Insufficient payload (model declined to judge)0.0100.003

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 head0.293
GPT teacher head0.437
Teacher spread0.145 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venue2019 Conference of the Canadian Society for the Study of EducationSame topicTeacher Education and Leadership StudiesFrench-language works237,207