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Record W3014446711 · doi:10.1177/1049732320910411

“I Look at You and See You Looking at Me”: Role Boundaries in a Dynamic Research Relationship in Qualitative Health Research With Refugees

2020· article· en· W3014446711 on OpenAlexaff
Sofie de Smet, Cécile Rousseau, Christel Stalpaert, Lucia De Haene

Bibliographic record

VenueQualitative Health Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsMcGill University
FundersBijzonder Onderzoeksfonds UGent
KeywordsGeneral partnershipRefugeeQualitative researchAgency (philosophy)HarmBoundary (topology)Space (punctuation)SociologyPsychologySocial psychologyPolitical scienceSocial scienceComputer science

Abstract

fetched live from OpenAlex

In institutional ethical and deontological guidelines, there is a prevailing, static understanding of the research partnership, with a clear boundary between researcher and participant. In this article, we argue that such a static understanding may run the risk of impeding the development of an enhanced contextual and dynamic intersubjective understanding of the research partnership and its impact on the growing importance of role boundaries in qualitative research. Drawing from a refugee health study on trauma and forced migration, we explore the different ways in which participants and the researcher engaged with the researcher's multiple positions and role boundaries. In doing so, we aim to contribute to a reflective research practice by providing tools to recognize signs of potential harm and offer potential vehicles of reconstruction and agency within the intersubjective space of a dynamic research relationship, within a continuous, shared renegotiation process of role boundaries.

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)0.451
metaresearch head score (Gemma)0.102
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4510.102
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.012
Science and technology studies0.0130.024
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.011
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 head0.706
GPT teacher head0.704
Teacher spread0.002 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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