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Record W3016402161

The Role of Reflexivity in Participatory Action Research to Empower Culturally Diverse Communities in Pakistan

2020· article· en· W3016402161 on OpenAlexvenueno aff
Hassan Raza

Bibliographic record

VenueJournal of rural and community development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsReflexivityParticipatory action researchAction researchEmpowermentContext (archaeology)SociologyCitizen journalismAction (physics)Public relationsPolitical scienceSocial sciencePedagogyGeographyAnthropology
DOInot available

Abstract

fetched live from OpenAlex

This article presents a real-world application of participatory action research (PAR) for effectively working with culturally diverse communities in Pakistan, based on a two-month project conducted with seven community-based organizations (CBOs) in one of the districts of the Punjab province in Pakistan. My process of transforming from a top-down approach to a PAR approach was grounded in critical self-reflection, observation, and reciprocal interaction. This transformation process increased my ability to understand community context and appreciate local knowledge, which in turn fostered collaboration, engagement, and collective learning. Although applying the PAR approach was not without challenges, complexities, and tension, it did result in local development. Hence, this paper explores the possibilities of PAR as an alternative approach to be considered by development agencies in their work with community partners. Keywords: reflexivity, participatory action research, culturally diverse communities, community empowerment

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)0.159
metaresearch head score (Gemma)0.086
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.841

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1590.086
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0130.050
Scholarly communication0.0170.011
Open science0.0030.017
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.731
GPT teacher head0.656
Teacher spread0.075 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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