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Record W4313396164 · doi:10.1111/var.12275

Collaborations across Cinematic Objects

2022· article· en· W4313396164 on OpenAlexaffabout
Cynthia Browne, Diana Allan, Merle Kröger, Philipp Scheffner, Vera Mader, Marion Biet, Theodor Frisorger, Anna Polze, J. P. Schadé

Bibliographic record

VenueVisual Anthropology Review · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsMcGill University
FundersDeutsche Forschungsgemeinschaft
KeywordsConversationFilmmakingReflexivityEthnographyMedia studiesVisual artsSociologyPower (physics)Art historyArtAnthropologyCommunicationMovie theater

Abstract

fetched live from OpenAlex

Abstract This conversation brings practitioners together from two different milieus of media production to initiate a dialogue about documentary practices as collaborative work, understood through a reflexive lens that also attends to the power relations and social differentiations inherent within its fabrication. As such, our conversation explores how filmmaking emerges through contingent and negotiated relations between filmmakers and film subjects, different representational modalities, the archive, (recording) technology and voice; the conversation also probes how the infrastructural conditions of collaborative work shape the ever‐shifting horizons of the documentary imagination. Mediated by members of the graduate research training group on Documentary Practices, based at the Ruhr University in Bochum, Germany, it features Philip Scheffner and Merle Kröger from pong, a production platform housed in Berlin, Germany, in conversation with Professor Diana Allan, a colleague of the Sensory Ethnography Lab based at Harvard University, a co‐organizer of the new Critical Media Lab at McGill University, and a Canada Research Chair in the Anthropology of Living Archives.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
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
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1260.001

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 head0.089
GPT teacher head0.426
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; a candidate call from one teacher head, not a consensus.

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

Citations0
Published2022
Admission routes2
Has abstractyes

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