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Record W3133085642 · doi:10.1111/sjtg.12359

Not just parenting in the field: Accompanied research and geographies of caring and responsibility

2021· article· en· W3133085642 on OpenAlexafffund
Christine Gibb

Bibliographic record

VenueSingapore Journal of Tropical Geography · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversity of TorontoInternational Development Research Centre
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDisciplinePoliticsIdentity (music)SociologyField (mathematics)Gender studiesMedia studiesSocial sciencePolitical scienceLawAesthetics

Abstract

fetched live from OpenAlex

Writinginour research companions, with attention to the importance of care in our fieldwork practices, is a political act that challenges the ways geography is believed to be practised, or should be practised. Once sidelined to footnotes and acknowledgements, research companions such as family members and research assistants have increasingly been rendered visible and their contributions considered. Yet, researchers remain reluctant to disclose their accompanied research in scholarly writing. Given this reticence, I contend that, collectively, such accounts are political acts and not warts‐and‐all disclosures of knowledge production. They challenge disciplinary norms over whose and which contributions count, and what constitutes a professional identity. Drawing upon Lynn Staeheli's (1996) insights into the potential for activism by transgressing boundaries of doing private acts in public spaces, and public acts in private spaces, I argue that doing and writing about accompanied fieldwork is fieldwork activism that re‐centres and values a caring geography.

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)0.022
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0140.051
Scholarly communication0.0110.014
Open science0.0020.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.266
GPT teacher head0.535
Teacher spread0.269 · 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.

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
Published2021
Admission routes2
Has abstractyes

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