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Record W3111613246 · doi:10.1177/1609406920977325

Capturing the Shadow and Light of Researcher Positionality: A Picture-Prompted Poly-Ethnography

2020· article· en· W3111613246 on OpenAlexaffabout
Anusha Kassan, Sarah Nutter, Amy R. Green, Nancy Arthur, Shelly Russell‐Mayhew, Monica Sesma-Vasquez

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsReflexivityEthnographyPrivilege (computing)Thematic analysisConversationSociologyQualitative researchShadow (psychology)PhotovoicePower (physics)Visual researchPsychologySocial scienceVisual artsAnthropologyComputer scienceCommunication

Abstract

fetched live from OpenAlex

Acknowledging researcher positionality and engaging in ongoing reflexivity are important components of qualitative research. In this manuscript, we share our experiences of examining our positionality and engaging in reflexive practice related to a research project with newcomer women in Canada. As a team of researchers from diverse backgrounds, we engaged in a picture-prompted poly-ethnographic conversation to better understand our attitudes, assumptions, and biases in relation to the topic of our research and gain a better understanding of what were asking of participants. Using thematic analysis, we uncovered four themes: 1) researchers bring multiple identities, 2) researchers bring privilege/power, 3) understanding what we call home, and 4) walking in participants’ shoes. We discuss these themes in detail, highlighting their implications for reflexive research with newcomer communities.

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)0.024
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.014
Scholarly communication0.0050.006
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.774
GPT teacher head0.699
Teacher spread0.075 · 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
DomainMethods
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

Citations17
Published2020
Admission routes2
Has abstractyes

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