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Record W4308644783 · doi:10.17742/image.tp.13.2.2

The Photographer Photographed: A Conversation with Jean Mohr

2022· article· en· W4308644783 on OpenAlexvenueno aff
Reuben Connolly Ross

Bibliographic record

VenueImaginations Journal of Cross-Cultural Image Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsConversationPortraitNarrativePhotographyVisual artsExperiential learningSociologyArtHistoryLiteraturePedagogy

Abstract

fetched live from OpenAlex

The Swiss photographer Jean Mohr, who died in November 2018 at the age of 93, is well known for his long career documenting the plight of the displaced and dispossessed. Especially noteworthy are his collaborations with major intellectual figures, through which he experimented with the construction of visual narratives. His celebrated books with John Berger include *A Fortunate Man*, an intimate portrait of an English country doctor, and A Seventh Man, a meditation on migrant labour in 1970s Europe; with Edward Said, he published After the Last Sky, a reflection on Palestinian life through the fusion of text and photography. Partially based on a short interview conducted with Mohr in early 2018, this paper reflects on his life and work, taking the reader on a journey mediated by our conversation. In particular, I explore the development of his unique approach to photography and the experimental construction of visual narratives. In so doing, I argue that Mohr’s work offers social scientists, particularly those engaged in studying processes of migration or zones of conflict, ways of constructing more effective, more engaged, and more experiential accounts of complex social realities.

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)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0200.011
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.329
GPT teacher head0.635
Teacher spread0.307 · 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 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
Published2022
Admission routes1
Has abstractyes

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