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Record W2600765419 · doi:10.1097/ans.0000000000000170

A Bicultural Researcher's Reflections on Ethical Research Practices With Muslim Immigrant Women

2017· article· en· W2600765419 on OpenAlexaff
Jordana Salma, Linda Ogilvie, Norah Keating, Kathleen F. Hunter

Bibliographic record

VenueAdvances in Nursing Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsSituatedAgency (philosophy)SociologyImmigrationGender studiesNarrativeIdentity (music)Economic JusticePsychologySocial psychologyPolitical scienceSocial scienceLawAesthetics

Abstract

fetched live from OpenAlex

Bicultural researchers are well positioned to identify tensions, disrupt binaries of positions, and reconcile differences across cultural contexts to ensure ethical research practices. This article focuses on a bicultural researcher's experiences of ethically important moments in research activities with Muslim immigrant women. Three ethical principles of respect, justice, and concern for welfare are highlighted, revealing the implications of binary constructions of identity, the value of situated knowledge in creating ethical research practices, and the need to recognize agency as a counterforce to oppressive narratives about Muslim women.

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)0.033
metaresearch head score (Gemma)0.038
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 score0.967
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0460.032
Scholarly communication0.0110.006
Open science0.0030.017
Research integrity0.0070.013
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 head0.513
GPT teacher head0.730
Teacher spread0.217 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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