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Record W4401445786 · doi:10.1177/14687941241264458

Designing afro-emancipatory qualitative research with and for Black people

2024· article· en· W4401445786 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

VenueQualitative Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaMcGill UniversityYork University
Fundersnot available
KeywordsQualitative researchSociologyGender studiesParticipatory action researchEpistemologySocial scienceAnthropology

Abstract

fetched live from OpenAlex

Since the tragic death of George Floyd in May 2020, there has been increased interest in anti-racist research. Consequently, several scholars are instigating qualitative inquiries in Black communities with limited preparation or expertise. This article presents a reflection regarding essential principles that can guide general and afro-emancipatory health and social sciences qualitative inquiries in Black diasporas. We contend that it is essential that researchers engage in reflexivity and consider Black ontologies, axiology and epistemologies. Furthermore, we propose the application of the following deontological principles to fulfil an ethical afro-emancipatory research framework: (a) include critical theories, (b) target the liberation of Afro-descendant peoples to enable their full participation as their whole selves in society; (c) ensure their leadership and meaningful involvement throughout the research process; (d) implement accountability mechanisms towards community members; (e) embrace intersectionality, an asset-based lens, and aspirational stance and; (f) foster healing, growth and joy.

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.

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)0.091
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
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 score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0910.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.581
GPT teacher head0.718
Teacher spread0.137 · 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