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Record W2051188766 · doi:10.1080/02560046.2013.855519

Visual ethnographies of displacement and violence: land(e)scapes in artists’ works at Thupelo Artists’ Workshop, Wellington, South Africa, 2012

2013· article· en· W2051188766 on OpenAlexaboutno aff
N. Jade Gibson

Bibliographic record

VenueCritical Arts · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyDisplacement (psychology)Visual artsSociologyVisual methodsGeographyAnthropologyMedia studiesArtPsychology

Abstract

fetched live from OpenAlex

This article draws together processes of art-making and academic ethnographic writing. It does this by including artists’ written comments on the personal and self-reflexive processes of artwork construction, as well as images of artworks, within academic discussion, in relation to emphasising the ‘turn’ within ethnography towards a more sensory, creative, emotive, embodied, interactive and performative approach. Consequently, the article functions as an exploration and illustration of what might constitute ‘ethnography’ in contemporary art, and art in ethnography, considering claims to similarity between the two. The focus of this multilayered article is on depictions of cultural, historical and corporeal violence in relation to land(e)scapes and self/culture/place and displacement, through the contributions of five artists who took part in a Thupelo International Artists’ workshop (emphasising the exchange of ideas, techniques and collaboration). Nineteen artists congregated in an isolated forest area in Wellington, South Africa, including the author in her capacity as both anthropologist and artist. Despite their different backgrounds, the artists drew on similar modes of working within visual ‘auto-ethnographies’ of socio-cultural displacement, in relation to collective violence, histories and conflict, operating as both ethnographers and archivists. Ultimately, through a consideration of overlaps between art and ethnography in relation to the works and auto-ethnographies depicted, it is suggested that this article, in occupying the ‘space between’ the disciplines, may also operate as an artwork.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0160.015
Scholarly communication0.0050.002
Open science0.0020.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.037
GPT teacher head0.309
Teacher spread0.272 · 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 designQualitative
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

Citations5
Published2013
Admission routes1
Has abstractyes

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