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Record W4413162384 · doi:10.4324/9781003461005-22

Photovoice

2025· book-chapter· en· W4413162384 on OpenAlexaboutno aff
Heidi Walker, Amber J. Fletcher, Maureen G. Reed, Nicholas Antonini

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoicePsychologyArtVisual arts

Abstract

fetched live from OpenAlex

Social path dependencies exist within climate institutions, such as local and regional institutions that respond to climate-related hazards. These dependencies, including masculine and Western cultural norms embedded in emergency response and climate adaptation planning, have contributed to an emphasis on technical, physical, and economic impacts and solutions. Impacts on social and more intangible values – and the diverse experiences of people who respond to hazards – often garner significantly less attention. Our role as feminist scholars is, in part, to build, model, and promote participatory tools that support change in policy, decisions, and practice within and across institutional levels. However, realising this potential will require more attention by researchers and other societal stakeholders and decision-makers to come together to facilitate meaningful dialogue and drive actions that break from path dependencies. Photovoice – a participatory research method – may be one such tool. Photovoice involves participants taking photographs that reflect specific aspects of their lived experiences and subsequently using those photos to foster critical reflection and collective dialogue around salient community issues. Drawing on two empirical studies involving community experiences of wildfire and flooding in Canada, this chapter discusses the opportunities and challenges of photovoice as a potential tool for countering gendered and hegemonic cultural path dependence in climate institutions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.668
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.004

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 head0.026
GPT teacher head0.300
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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