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Record W2155252308 · doi:10.46743/2160-3715/2011.1299

Participatory and Action-Oriented Dissertations: The Challenges and Importance of Community-Engaged Graduate Research

2014· article· en· W2155252308 on OpenAlexafffund
Emily van der Meulen

Bibliographic record

VenueThe Qualitative Report · 2014
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of CanadaOntario Ministry of Health and Long-Term Care
KeywordsParticipatory action researchAction researchSociologyCitizen journalismIdeologyAction (physics)Isolation (microbiology)Graduate studentsPublic relationsPedagogyEngineering ethicsPolitical scienceEngineeringPolitics

Abstract

fetched live from OpenAlex

Graduate students commonly experience isolation and estrangement when conducting their final research projects, which can contribute to difficulties in completion. A creative and socially beneficial way to offset academic isolation is for graduate students to engage in participatory and action-oriented research projects with local communities. Facilitating a research study with a local partner can be a richly rewarding experience. This article argues that students who enjoy working in collaborative environments and want their final research projects to lead to beneficial social change can find fulfillment in action research (AR) methodologies. Critiqued by some for its lack of tangible and practical methods and its over-reliance on ideology, others, including the author, argue that the benefits of participatory research far outweigh the challenges.

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)0.271
metaresearch head score (Gemma)0.287
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.729
Threshold uncertainty score0.899

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2710.287
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0190.038
Scholarly communication0.0260.015
Open science0.0050.021
Research integrity0.0070.013
Insufficient payload (model declined to judge)0.0040.001

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 head0.905
GPT teacher head0.687
Teacher spread0.218 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations41
Published2014
Admission routes2
Has abstractyes

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