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Record W2904511499 · doi:10.3138/anth.2017-0006

Introduction: Ethnography, Performance and Imagination

2018· article· en· W2904511499 on OpenAlexaffvenue
Magdalena Kazubowski‐Houston, Virginie Magnat

Bibliographic record

VenueAnthropologica · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaYork University
Fundersnot available
KeywordsEthnographySociologyReflexivityEmbodied cognitionThe artsCitizen journalismEpistemologyAestheticsAnthropologyMedia studiesVisual artsComputer scienceArt

Abstract

fetched live from OpenAlex

This introduction to the thematic section entitled “Ethnography, Performance and Imagination” explores performance as “imaginative ethnography” (Elliott and Culhane 2017), a transdisciplinary, collaborative, embodied, critical and engaged research practice that draws from anthropology and the creative arts. In particular, it focuses on the performativity of performance (an event intentionally staged for an audience) employed as both an ethnographic process (fieldwork) and a mode of ethnographic representation. It asks: can performance help us research and better understand imaginative lifeworlds as they unfold in the present moment? Can performance potentially assist us in re-envisioning what an anthropology of imagination might look like? It also inquires whether working at the intersections of anthropology, ethnography, performance and imagination could transform how we attend to ethnographic processes and products, questions of reflexivity and representation, ethnographer-participant relations and ethnographic audiences. It considers how performance employed as ethnography might help us reconceptualise public engagement and ethnographic activism, collaborative/participatory ethnography and interdisciplinary research within and beyond the academy. Finally, this introduction provides a brief overview of the contributions to this thematic section, which address these questions from a variety of theoretical, methodological and topical standpoints.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.006
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.428
GPT teacher head0.625
Teacher spread0.197 · 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

Citations10
Published2018
Admission routes2
Has abstractyes

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