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Record W2238968637 · doi:10.1177/0263775815604922

Animal performativity: Exploring the lives of donkeys in Botswana

2015· article· en· W2238968637 on OpenAlexafffund
Martha Geiger, Alice J. Hovorka

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Guelph
KeywordsDonkeyPerformativityLivelihoodSociologyContext (archaeology)WelfareStructural functionalismGender studiesSocial sciencePolitical scienceGeographyAgricultureBiologyEcology

Abstract

fetched live from OpenAlex

Donkeys provide affordable and accessible means of transport, draught power and food security for smallholder farmers in and around Maun, Botswana. Their role and welfare is often compromised by people's extensive use of and inability to care for their animals given their individual or broader circumstances. Our paper explores the lives of donkeys and donkey-human relations in Botswana. We apply a feminist posthumanist iteration of performativity to illustrate and explain who the donkey is, what they experience, and the context within and through which these performances are constituted. Methodologically we merge tools from animal welfare science with social science to unearth donkey physical and emotional states of being, as well as the ways in which humans use, care for, and value donkeys in this particular context. Our findings reveal donkey subjectivities (experiences) characterized by relative drudgery, hardship, and compromised physical and emotional welfare; donkey subjects (identities) grounded in their marginalized status within government and everyday livelihood realms; and donkey spatiality (contextual factors) emerging from their performances as working animals, lesser than cattle, and pathways out of poverty. Contributions of our work include empirical insights on donkey-human relations, theoretical exploration of animal performativity, and methodological innovation investigating the lives of animals.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.066
GPT teacher head0.282
Teacher spread0.216 · 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.

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

Citations47
Published2015
Admission routes2
Has abstractyes

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