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Record W4294957974 · doi:10.14506/ca37.3.11

Why Do “Good” Pictures Matter in Anthropology?

2022· article· en· W4294957974 on OpenAlexfundno aff
Camilo León-Quijano

Bibliographic record

VenueCultural Anthropology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
FundersCentre National de la Recherche ScientifiqueSociety for Visual AnthropologyÉcole des Hautes Etudes en Sciences Sociales
KeywordsRepresentation (politics)EthnographySociologySubject (documents)Object (grammar)HumanitiesVisual anthropologyExperiential learningPoliticsAnthropologyArtPhilosophyLinguisticsPolitical science

Abstract

fetched live from OpenAlex

This article explores the relationship between photography and anthropology in the age of digital ethnographies and anthropologies of the future. It focuses on the phenomenological bond between the picture-taking process and the politics of visual representations by looking at an object that has shaped the discipline since its very origins. Based on a series of visual encounters in a French banlieue, I describe to what extent good pictures are relative, incomplete, uncertain, sometimes inconsistent, and contain contradictory objects interacting with existing cultural and photographic conventions. I argue that good pictures are experienced pictures that go beyond the realm of a photograph. To this end, I consider the material and experiential connections between photography, sound, and text. Finally, I discuss how anthropologists’ pictorial choices redefine the material and experiential ties to photographic materials. From a critical standpoint, a good picture might challenge the politics of visual representation of the imaged subject through both a photographic and ethnographic engagement. RÉSUMÉ Cet article explore la relation entre la photographie et l’anthropologie à l’ère des ethnographies numériques et des anthropologies du futur. Il examine le lien entre le processus de prise de vue et la politique des représentations visuelles en s’intéressant à un objet qui a façonné la discipline depuis ses origines. Suivant une série de rencontres dans une banlieue française, je décrirai dans quelle mesure les bonnes images peuvent être des objets incomplets, relatifs, incertains, parfois incohérents et contradictoires qui interagissent avec des conventions culturelles et photographiques existantes dans le milieu étudié. J’affirme que les bonnes images sont des images « expérimentées ». J’analyse en quoi les choix plastiques des anthropologues redéfinissent les liens matériels et expérientiels avec les matériaux photographiques issus de l’enquête de terrain. D’un point de vue critique, une bonne photo peut remettre en question la politique de représentation visuelle du sujet imagé, par un double engagement à la fois photographique et ethnographique. RESUMEN Este artículo explora la relación entre la fotografía y la antropología en la era de etnografías digitales y antropologías del futuro. El texto analiza el vínculo fenomenológico entre el proceso de realización fotográfica y la política de representación visual mediante el estudio de un objeto que ha forjado la disciplina desde sus orígenes. A partir de una serie de encuentros visuales en un suburbio francés, describiré hasta qué punto las buenas imágenes son objetos relativos, incompletos, inciertos, a veces incoherentes y contradictorios que interactúan con convenciones culturales y fotográficas existentes. Las buenas imágenes son imágenes “experimentadas” que van más allá de la fotografía. Para ello, considero las conexiones materiales y experienciales entre la fotografía, el sonido y el texto. Des ésta manera analizo cómo las decisiones plásticas de los antropólogos redefinen los vínculos materiales y experienciales con los materiales fotográficos. Desde un punto de vista crítico, una buena imagen puede desafiar la política de representación visual del sujeto representado a través de un compromiso tanto fotográfico como etnográfico.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1350.000

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 head0.029
GPT teacher head0.366
Teacher spread0.337 · 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
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

Citations20
Published2022
Admission routes1
Has abstractyes

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