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Record W2971765347

Annotated Bibliography: Disability Studies and the place of diversity within the Scholarship of Teaching and Learning

2019· article· en· W2971765347 on OpenAlexaff
Joanna Rankin, Sarosh Sawani

Bibliographic record

VenueThe Journal for Research and Practice in College Teaching · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDiversity (politics)ScholarshipContext (archaeology)Scholarship of Teaching and LearningRelevance (law)Learning disabilityDisability studiesSocial justiceInclusion (mineral)Annotated bibliographySociologyField (mathematics)PedagogyPsychologyLibrary scienceSocial scienceTeaching methodPolitical scienceTeaching and learning centerComputer scienceGeographyGender studiesAnthropology
DOInot available

Abstract

fetched live from OpenAlex

This annotated bibliography has been shaped by the recognition of a relationship between the contemporary focus of diversity and social justice in SoTL and the role of teaching and learning in the field of Disability Studies. Considering the relevance of SoTL to the study of disability and to students and faculty with disabilities, this selection of literature identifies key topics that take up current teaching and learning theories and practices around diversity and social justices, as well as pointing to multiple intersections between these two areas. Specifically, readings included in this bibliography provide an overview of current literature in SoTL and Disability Studies and identify a recent heightened interest in the pursuit of social justice and diversity in post-secondary environments. Annotations review the bases of these two philosophies, as they relate to teaching and learning, explore the role of post-secondary students with disabilities in this context and provide a discussion of future directions

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)0.001
metaresearch head score (Gemma)0.009
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: Review · Consensus signal: Review
Teacher disagreement score0.045
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0120.026
Science and technology studies0.0040.002
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0450.009

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 head0.238
GPT teacher head0.515
Teacher spread0.277 · 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
GenreReview

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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