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Record W4387298193 · doi:10.1177/16094069231204820

A Qualitative Multi-Methods Research Protocol: Applied Research Ethics in the Middle East North Africa Region

2023· article· en· W4387298193 on OpenAlexfundno aff
Jihad Makhoul, Catherine El Ashkar, Rima Nakkash, Sonja Bjelobaba

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsResearch ethicsDeskHuman researchMiddle EastQualitative researchProtocol (science)Focus groupPolitical scienceEngineering ethicsGeographySociologySocial scienceMedicineEngineeringLawAlternative medicineAnthropology

Abstract

fetched live from OpenAlex

In generating new knowledge in all fields related to human subjects research, research ethics is key. The Middle East and North Africa (MENA) region has witnessed a remarkable increase in research involving human participants, but robust contextually relevant guidelines and local capacity to guide ethical research are lacking. The research protocol presented and discussed here represents the methodology used to assess the landscape of applied research ethics in the region from the narratives of several constituencies in the research process, namely researchers, research ethics committee chairs and directors of research institutions. The study is a three-year multi-phase, multi-method research which involved a sequence of phases starting with a desk review, writing country reports, focus groups, and in-depth interviews, followed by a regional survey. The lead research team worked with country teams in 6 sites in the MENA region to conduct the empirical research which will be described in detail and reflected on for rigor and challenges.

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)0.701
metaresearch head score (Gemma)0.237
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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: Methods · Consensus signal: Methods
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.7010.237
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0020.007
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0000.009
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 head0.983
GPT teacher head0.825
Teacher spread0.158 · 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
GenreMethods

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

Citations5
Published2023
Admission routes1
Has abstractyes

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