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Record W4385745938 · doi:10.59962/9780774824460

Photography, Memory, and Refugee Identity

2013· book· en· W4385745938 on OpenAlexaboutno aff
Lynda Mannik

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2013
Typebook
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeIdentity (music)PhotographyArtVisual artsArt historyHistoryAestheticsArchaeology

Abstract

fetched live from OpenAlex

On 13 December 1948, a small ship carrying 347 Estonian refugees fleeing Soviet rule arrived at Pier 21 in Halifax. In Photography, Memory, and Refugee Identity, anthropologist Lynda Mannik analyzes the refugee experience through the photographic record of those who made that harrowing voyage across the Atlantic more than sixty years ago. Drawing on a collection of photographs taken during the voyage and at the Pier 21 detention centre, Mannik asks surviving passengers to describe their migration, their reception in Canada, and their feelings about the terms refugee and boat person. She explores to what extent the photos reflect the passengers’ experiences as they remember them and how those experiences compare with representations of refugees in news media, in government rhetoric, and at the Pier 21 Museum in Halifax. Ultimately, Mannik demonstrates that the photographs in the SS Walnut collection bear witness to the refugee experience even as the meanings attached to them have changed over time and in shifting contexts.

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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.005
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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 head0.019
GPT teacher head0.190
Teacher spread0.170 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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