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Record W2894110342 · doi:10.5539/ies.v11n10p96

An Investigation into the Relationship between Adults’ Levels of Education-Related Epistemic Freedom and Epistemic Violence

2018· article· en· W2894110342 on OpenAlexvenueno aff
Osman Yılmaz Kartal, Akan Deniz Yazgan, Esranur AVCI

Bibliographic record

VenueInternational Education Studies · 2018
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsnot available
Fundersnot available
KeywordsEpistemologySociologyPhilosophy

Abstract

fetched live from OpenAlex

The present study investigates the relationship between epistemic freedom and epistemic violence. The problematization was based on adults. Due to adults’ responsibilities for education, the study focuses on adults’ levels of education-related epistemic freedom and epistemic violence. The research problem was analyzed with the correlational research model. The sample consists of 129 participants between 22 and 67 years. The data were collected with epistemic violence-freedom scale. The study revealed that adults’ level of accepting education-related epistemic violence and resorting to education-related epistemic violence were “moderate” and “low”, respectively, while their enjoyment of epistemic freedom in the past was between “moderate” and “high” and their tendency to education-related epistemic freedom was “high”. The authors found a significant, negative, and weak relationship between adults’ levels of “resorting to epistemic violence” and levels of “enjoyment of education-related epistemic freedom in the past” and “their tendency to education-related epistemic freedom”. The authors also observed a significant, positive, and moderate relationship between adults’ levels of “enjoyment of education-related epistemic freedom in the past” and “their tendency to education-related epistemic freedom”. The authors suggest that individuals should be provided with a freedom-based education and setting.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.122
GPT teacher head0.435
Teacher spread0.312 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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