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Record W2544011624 · doi:10.1111/ruso.12143

Knowledge Equity is Social Justice: Engaging a Practice Theory Perspective of Knowledge for Rural Transformation

2016· article· en· W2544011624 on OpenAlexaff
JoAnn Jaffe

Bibliographic record

VenueRural Sociology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPraxisSociologyTransformative learningEquity (law)Traditional knowledgeNarrativePerspective (graphical)Social justiceEpistemologySocial sciencePublic relationsEngineering ethicsPedagogyPolitical scienceIndigenousEcologyComputer science

Abstract

fetched live from OpenAlex

Abstract Social inequities are made possible by and compounded by knowledge inequity. Accordingly, new and more vehicles are needed in which different and transformative knowledges can chart new possibilities, practices, and meanings for rural people. One way forward is to work toward an ecology of knowledges in which the need for many types of knowledge is recognized and different knowledges are respected. Drawing on case study and “photo‐voice” research with women in rural Ethiopia, this article uses a practice theory approach to explore the possibilities of knowledge dialogue among different types of knowledge and skill. Recognizing the wide spectrum of deep knowledge and skill employed in local practice, and understanding how all knowledges are rooted in social context, actors can find common ground to dialogue through methods of praxis and narrative.

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)0.021
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0120.082
Scholarly communication0.0190.016
Open science0.0020.015
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.104
GPT teacher head0.501
Teacher spread0.397 · 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 designTheoretical or conceptual
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

Citations13
Published2016
Admission routes1
Has abstractyes

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