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Record W2905502578 · doi:10.4324/9781315276953-4

Residential School Photographs

2018· book-chapter· en· W2905502578 on OpenAlexaboutno aff
Carol Williams

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyOptometryVisual artsMedicineArt

Abstract

fetched live from OpenAlex

The de-territorialisation of Native North American Indians, their confinement in bounded reservations, and the forced re-education of children in the residential school system between 1889 and the 1960s point to settler colonialism’s investment in Indigenous immobility. Within this context, photographs of Indigenous subjects attending residential schools emerged as a distinct genre that redefined mobility and progress in terms of assimilation. These pictures only superficially capture the violence enacted by residential schools, a process that often began with a child’s abrupt removal from home, followed by incarceration, sickness, and death. Comparing archives from western Canada and the United States, this chapter shows how and why photographs of residential schools expose the state’s intention to disassociate Indigenous children from their attachments to territory, kin, and culture. In Canada, these experiences have been animated through oral testimonies and photographic representation of psychological and physical disenfranchisement, which together serve as evidence in the advocacy for contemporary political redress.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.266
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2660.050

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 head0.573
GPT teacher head0.623
Teacher spread0.050 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2018
Admission routes1
Has abstractyes

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