MétaCan
Menu
Back to cohort
Record W4293796892 · doi:10.14738/assrj.98.12931

Discovering How to Do Reflexivity and Self-Reflexivity: A Longitudinal Empirical Research Findings

2022· article· en· W4293796892 on OpenAlex
Emmanuelle De Verlaine

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

VenueAdvances in Social Sciences Research Journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsReflexivityPerspective (graphical)PsychologyAction (physics)EpistemologyFeelingSocial psychologySociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Reflexivity is known to be a mental process where a person takes distance to oneself to analyze and take a critical perspective over own feelings, actions and intentions in order to realign own practice. Reflexivity is therefore a form of metacognitive brain functionality reaching a state of mind’s sense of acute awareness. The reflexivity’s functionality has been recognized as valuable to improve professional practices. The main gap in research and literature is to explicate how to do reflexivity and most of all, how to apply it to all aspects of human life toward self-actualization. This research aims at answering at: How to Do reflexivity and Self-Reflexivity? To answer this question a 17 year-long longitudinal Action-Research investigations reveals how to learn and practice reflexivity. This paper also reveals how reflexivity can be applied to aim at one’s well-being and self-actualization. The discussion addresses the long-term impact of practicing reflexivity coupled with mindfulness as an ability to reach self-liberation.

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)0.062
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0620.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0320.001
Scholarly communication0.0000.001
Open science0.0010.004
Research integrity0.0000.008
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 head0.513
GPT teacher head0.680
Teacher spread0.167 · 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