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Record W1603273306 · doi:10.1177/160940691201100208

Ethics in Qualitative Research: A View of the Participants' and Researchers' World from a Critical Standpoint

2012· article· en· W1603273306 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBeneficenceTransparency (behavior)Research ethicsEngineering ethicsRespect for personsEconomic JusticeQualitative researchVocabularySociologyPsychologyAutonomySocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

This paper illustrates how certain ethical challenges in qualitative research necessitate sustained attention of two interconnected worlds: the world of the researcher and the world of the participant. A critical view of some of the ethical challenges in the participants' and researchers' world reveals that how we examine both these worlds' effects how we design our research. In addition, it reflects the need for researchers to develop an ethical research vocabulary at the inception of their research life through multiple modes. The modes may include dialogue in the spoken and written and visual to affect their aims to adhere to the principles of respect, beneficence, nonmaleficence, and justice in a way that is mutually beneficial to the participant and the researcher. Further, the deliberations in this paper reveal that a critical conscious research ethics are embedded in the unfolding research ethics process involving the participants and the researchers, and both the participant and researcher add equal weight to the transparency of the ethical process and add value to building methodological and ethical rigor to the research.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaResearch integrity
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.418
metaresearch head score (Gemma)0.328
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.378
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4180.328
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.007
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.969
GPT teacher head0.833
Teacher spread0.136 · 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