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Record W4400419308 · doi:10.3224/ijar.v20i1.05

From Participatory Research to the Co-construction of Actions – Reflections on how to Reinforce Action Research for Social Inclusion

2024· article· en· W4400419308 on OpenAlexaboutno aff
Isabel Heck

Bibliographic record

VenueIJAR – International Journal of Action Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsParticipatory action researchAction researchInclusion (mineral)SociologySocial researchCitizen journalismAction (physics)Engineering ethicsEpistemologySocial sciencePolitical sciencePedagogyEngineeringAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

An important part of the action research literature focuses on the participatory dimension of the research process and is much less explicit on the connection of research and action or on how researchers contribute to tangible transformations, in particular outside organizational or education settings. Drawing from seven years of experience as an action researcher within an anti-poverty organization dedicated to improving living conditions in a low-income neighborhood in Montreal (Canada), this article seeks to enhance our comprehension of how action researchers can more effectively contribute to transformational action. Our study identifies four primary functions of research within the examined model and underscores three core characteristics to strengthen the integration of knowledge production and action. These characteristics encompass expanding the role of researchers to actively participate in both the co-development and implementation of action; engaging in long-term commitments and partnerships in a given setting, preferably being even a researcher based in the setting; and fostering collaborations with universities. By elucidating these key elements, this article intends to offer insights into improving the impact of action research, ultimately advancing our ability to contribute to transformative change for more inclusive and sustainable societies.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.057
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0570.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.952
GPT teacher head0.810
Teacher spread0.142 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Theoretical or conceptual
DomainMethods
GenreEmpirical · Methods

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

Citations2
Published2024
Admission routes1
Has abstractyes

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