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Record W2071815905 · doi:10.1525/jer.2013.8.4.28

Extending the Olive Branch: Enhancing Communication and Trust Between Research Ethics Committees and Qualitative Researchers

2013· article· en· W2071815905 on OpenAlexafffund
Suzanne McMurphy, Jacqueline Lewis, Pierre Boulos

Bibliographic record

VenueJournal of Empirical Research on Human Research Ethics · 2013
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of Windsor
FundersUniversity of Windsor
KeywordsTransparency (behavior)Engineering ethicsResearch ethicsQualitative researchConstructiveProcess (computing)Research integrityPerspective (graphical)Public relationsPsychologySociologyPolitical scienceComputer scienceLawSocial scienceEngineering

Abstract

fetched live from OpenAlex

Using data from a study of qualitative researchers' experiences with ethics review and our own lens as both researchers and REB/IRB members, we explore the ethics review process and provide recommendations for improvements. Our findings suggest that the review process would benefit from a strengthened trust relationship between REB/IRBs and qualitative researchers that would require a commitment from both sides. Regarding REBs/IRBs, increased transparency of the review process, consistent application of federal guidelines, and a more collaborative review approach may improve the trust of qualitative researchers. Regarding researchers, approaching ethics review as a form of academic peer review, similar to other types of assessments of scholarly products such as grants and publications, may promote the integration of ethics review as an intrinsic part of the research process. Recognizing that responsibility for ethical research is a shared goal of both researchers and REB/IRBs, improved collaboration and constructive interaction can assist in understanding each other's perspective and work toward the development of mutual trust and respect.

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

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
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
models agreeAgreement 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)0.546
metaresearch head score (Gemma)0.624
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5460.624
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0090.027
Scholarly communication0.0020.001
Open science0.0030.004
Research integrity0.0030.163
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 head0.970
GPT teacher head0.805
Teacher spread0.165 · 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

Labeled directly by 2 models reading the full record.

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

Citations15
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Empirical Research on Human Research EthicsSame topicEthics in Clinical ResearchCategoryMetaresearchFrench-language works237,207