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Record W3140772997 · doi:10.1080/14733285.2021.1907311

Feminist ethicality in child-animal research: worlding through complex stories

2021· article· en· W3140772997 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChildren s Geographies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsScholarshipSociologyFocus (optics)EthnographyMeaning (existential)Gender studiesEpistemologyAnthropologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Thinking with feminist scholarship on ethicality, this article draws from two ethnographies with animal and young children to outline new questions for doing research in children’s geographies. Specifically, the article discusses how feminist ethicality within multispecies research challenges the masculinist idea that ethical research should focus on children’s story-making and ability to make meaning of the world. Instead, the authors call for an ethical focus on worlding processes or the making of worlds, and to seek possibilities for recuperation in the midst of children and more-than-human relations. The article concludes by reconfiguring the relations between ethics and research with young children, asking for a focus on what might be possible in the shaping of the present and future.

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.

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)0.012
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0020.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.748
GPT teacher head0.661
Teacher spread0.087 · 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