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Record W4283835150 · doi:10.1177/10497323221112620

The Emotional and Psychological Labor of Insider Qualitative Research Among Systemically Marginalized Groups: Revisiting the Uses of Reflexivity

2022· article· en· W4283835150 on OpenAlexaff
David J. Kinitz

Bibliographic record

VenueQualitative Health Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsInsiderReflexivityOpenness to experienceRelevance (law)Equity (law)SociologyEmbodied cognitionPublic relationsPsychologyInclusion (mineral)Diversity (politics)Qualitative researchSocial psychologyPolitical scienceSocial scienceEpistemology

Abstract

fetched live from OpenAlex

In response to decades-long exclusionary practices, academic institutions are now recruiting early career researchers (ECRs) from systemically marginalized populations who specialize in equity-related research. As a result, these ECRs are likely to conduct research within their communities on topics that have personal relevance-insider research. Methodological training for insider research places an emphasis on methods, such as reflexivity, to ensure rigor; however, the emotional and psychological impacts of these research methods on the researcher are seldom discussed. Therefore, I use analytic autoethnography to illustrate the embodied impacts of conducting insider research using an example of personal relevance and argue that methodological practices require an embodied reflexivity that centers the researcher and the impacts the research has on them. This paradoxically rewarding and taxing work necessitates changes in methodological training and practice, institutional support, and an openness to innovation when calling for equity, diversity, and inclusion in the academy.

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)0.515
metaresearch head score (Gemma)0.082
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5150.082
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.004
Science and technology studies0.0100.021
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.004
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 head0.865
GPT teacher head0.765
Teacher spread0.100 · 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; both teacher heads agree on what is shown here.

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

Citations35
Published2022
Admission routes1
Has abstractyes

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