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Record W4388961831 · doi:10.1016/j.emospa.2023.100990

Navigating the emotion-embodiment-language nexus in international research: Stories from a foreign researcher and local interpreter

2023· article· en· W4388961831 on OpenAlexfundno aff
Josie Wittmer, Mubina Qureshi

Bibliographic record

VenueEmotion, space and society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
FundersUniversité de LausanneSocial Sciences and Humanities Research Council of CanadaQueen's University
KeywordsNexus (standard)SociologyEmbodied cognitionInterpreterInterpretation (philosophy)SubjectivityPower (physics)Field (mathematics)LinguisticsPsychologyEpistemologyComputer science

Abstract

fetched live from OpenAlex

Feminist researchers engage reflexively with questions of how power operates through intersubjective processes like building rapport, obtaining consent, and being accountable in the ‘field.’ But how do researchers build these connections across embodied and linguistic differences in interlingual research involving local interpretation? In this paper, we delve into our experiences as a foreign researcher and a local interpreter conducting interviews and group discussions with low-income women waste workers in India. We focus on our co-navigations of positionality and power with a focus on language, emotion, and embodiment in connecting with participants and reflect on how interpretation and translation processes can mediate, complicate, and enrich connection-building. We argue that emotional, embodied, and linguistic challenges and opportunities are not uniformly experienced between differently positioned team members and require space to grapple with divergent experiences, understandings, and outcomes that emerge across this nexus. We detail three research encounters, analyzing the nuances of positionality in our divergent roles; our navigations of care and refusal manifesting across the triple subjectivity of encounters; and our strategies for working across languages, embodiment, and emotion in the colonial past-present. The paper contributes to feminist, anti-colonial methodologies by providing insights into our experiences of connection-building in the ‘field’ and revealing the ‘scaffolding’ work and relations which support our processes and pursuits of ethnographic research, translation, and accountability.

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)0.018
metaresearch head score (Gemma)0.023
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 score0.970
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0300.055
Scholarly communication0.0160.015
Open science0.0030.017
Research integrity0.0050.013
Insufficient payload (model declined to judge)0.0030.001

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 head0.213
GPT teacher head0.541
Teacher spread0.328 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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