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Record W2915437935

People in Transit: Expanding the Spatial and Temporal Frames of the American Anthropological Association Annual Meetings

2018· article· en· W2915437935 on OpenAlexaff
Justin Raycraft

Bibliographic record

VenueVisual Ethnography · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsNarrativeEphemeral keyWhite (mutation)Event (particle physics)Visual artsHistoryAssociation (psychology)Media studiesPoliticsSociologyArtPolitical sciencePsychologyComputer scienceLawLiterature
DOInot available

Abstract

fetched live from OpenAlex

This photo essay comprises a series of black and white photographs taken in transit. The photographs were taken in airports, planes, busses, railway platforms and underground metro stations during the photographer’s journey to the 2017 American Anthropological Association (AAA) Annual Meeting in Washington, DC. Taken in high contrast, the images presented here reflect the photographer’s acute awareness of the sharp conceptual boundaries that separate the scholarly arena located inside of the venue’s walls from the social, political, economic and spatial worlds that exist outside of them. The essay provides a visual narrative of the photographer’s observations of people and places while on route to the event. In doing so, it highlights everyday lived experiences that occurred “just before” the official onset of the event, while “on the way” to the venue. Through careful attention to shadows and viewpoint, the photographer subtly anonymizes subjects, maintaining the fabric of their relationships as passing strangers. While at once a reflexive commentary on the temporal and spatial frames of conferences, the essay also documents the diverse ways that people temporarily dwell in ephemeral travel spaces.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
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 head0.021
GPT teacher head0.373
Teacher spread0.352 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2018
Admission routes1
Has abstractyes

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