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Record W4404290317 · doi:10.1177/14407833241283154

Visualising truth-telling through Indigenous community-specific vernacular photography in Canada and Australia

2024· article· en· W4404290317 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of sociology · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of Regina
FundersAustralian Research Council
KeywordsIndigenousVernacularPhotographySociologyVisual methodsAnthropologyAestheticsMedia studiesGender studiesSocial scienceGeographyVisual artsArtLiteratureEcology

Abstract

fetched live from OpenAlex

The emphasis in Indigenous photographic scholarship has largely been on Indigenous subjects viewed through a colonial lens. It is often assumed that impoverished communities did not have cameras or photographic archives, given the vulnerability and mobility of their lives. However, cameras, although scarce, were present. This is demonstrated in the photographic legacies of Ngarrindjeri families in south-eastern Australia and Qu’Appelle Valley Métis families in Saskatchewan, Canada, investigated in this article. Both groups share similar histories in marginalised settings – ‘one mile camps’ in Australia and ‘Road Allowance’ communities in Canada. The archives created by generations of Indigenous photographers are both familiar and unique. They depict smiling groups posed in front of cars and homes, although the backdrops are very different to the middle-class and suburban settings typical of vernacular photography more widely. Photographic archives in these communities are comparatively sparse, and thus more precious. Importantly, we see the matriarchs who anchored large, extended families, and evidence of their Indigenous knowledges and the survival skills that provided for them. Working with these photographs in deep engagement with communities and their long-held knowledge reanimates these images in contemporary contexts to facilitate the reclaiming of land, connection and family. We argue that such images represent unparalleled forms of truth-telling, offering a nuanced visual history unavailable from other sources.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.480

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)0.0000.000

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 head0.174
GPT teacher head0.295
Teacher spread0.121 · 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