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Record W3194988348 · doi:10.22329/csw.v21i1.6226

Transformative Consciousness

2020· article· en· W3194988348 on OpenAlexvenueno aff
Alexis Jemal, Sarah Ross Bussey, Keith G. Davis

Bibliographic record

VenueCritical Social Work · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute on Drug Abuse
KeywordsTransformative learningConceptualizationPsychologyScale (ratio)ConsciousnessPhotovoiceSocial psychologyArtificial intelligenceComputer scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

This paper outlines the development of the Transformative Consciousness (TC) of Oppression and Privilege (COAP) Scale created to address the conceptual and measurement limitations of the critical consciousness (CC) construct. Unlike prior CC measures, this scale was developed for the general population, integrates identities that are oppressed and privileged, incorporates the social-ecological framework, assesses cognitions, and attempts to reduce the impact of social desirability bias. Following DeVellis’ (2003) scale development process and Rubio and colleague’s (2003) process for content validity, this paper presents: a review of CC measurement literature and the lack of standardized conceptualization and measurement tools; an overview of TC theory; the COAP scale development process; and, a content validity study of COAP including quantitative and qualitative methods. An outgrowth of the first author’s conceptualization of Transformative Consciousness, the domain-specific and content validated COAP scale demonstrates a unique scaling method combining vignettes, sentence completions, rank ordering of response options, and scoring of ordering patterns. Limitations of the COAP scale and opportunities for future research are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.016
Scholarly communication0.0060.006
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.058
GPT teacher head0.367
Teacher spread0.309 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
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

Citations5
Published2020
Admission routes1
Has abstractyes

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