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Record W2152880433 · doi:10.7202/039662ar

Image Construction as a Strategy of Resistance by Progressive Community Organizations

2010· article· en· W2152880433 on OpenAlexaffvenue
Purnima George, Ken Moffatt, Lisa Barnoff, Brienne Coleman, Cathy Paton

Bibliographic record

VenueNouvelles pratiques sociales · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsSocial Sciences and Humanities Research CouncilToronto Metropolitan University
Fundersnot available
KeywordsResistance (ecology)Presentation (obstetrics)Service (business)Power (physics)Work (physics)Public relationsBusinessPolitical scienceMarketingEngineeringMedicine

Abstract

fetched live from OpenAlex

This article presents research findings on image construction as a strategy of resistance used by progressive community agencies to be responsive to the increasing marginalization of their service users in current times. The agencies project nuanced images in representing their work to service users, funders and stakeholders and community partner agencies. These nuanced images serve to demonstrate the multiple and complex identities of these agencies. The agencies have used this strategy successfully to reclaim their power with funders and use their power effectively in making their services responsive and relevant to the situations of service users. The article provides an interesting presentation on the dynamics of the use of this strategy by progressive community organizations.

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 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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.226
GPT teacher head0.564
Teacher spread0.338 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2010
Admission routes2
Has abstractyes

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