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Record W4400741196 · doi:10.1080/14733285.2024.2371000

From ‘No’ to ‘Know’: a heuristic for decolonizing research with youth

2024· article· en· W4400741196 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChildren s Geographies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaInternational Development Research Centre
KeywordsHeuristicNeed to knowSociologyComputer scienceArtificial intelligenceComputer security

Abstract

fetched live from OpenAlex

This paper addresses epistemic violence in social science research, drawing on a multiyear study with marginalized teenagers in Old Havana, Cuba to articulate an onto-epistemological approach to knowledge production that can contribute to the decoloniality of knowledge production. Building on decolonial, feminist, Indigenous, and poststructuralist theories, the heuristic presented here contributes an alternative to conventional positivist understandings of knowledge, by defining knowledge as social, created, performed and resistant, and illustrates how these theoretical tenets can be made material in research practice, in this case through the use of arts-based methods. Responding to calls to decolonize knowledge within the field of children’s geographies and adjacent disciplines, this paper addresses the attendant need to reconceptualize what counts as knowledge and identify methodological innovations to support the achievement of these changes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.381
Teacher spread0.330 · 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