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Record W7021145249

The more you talk, the worse it is: Student perceptions of law and authority in schools

2016· article· en· W7021145249 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Discipline and Inequality
Canadian institutionsnot available
FundersYork University
KeywordsDisciplinePerceptionWork (physics)School disciplineAssociation (psychology)Process (computing)Variation (astronomy)Qualitative research
DOInot available

Abstract

fetched live from OpenAlex

Prior works have established the association between students’ perceptions of school discipline and both behavioral and academic outcomes. The interplay between disciplinary fairness and students’ perceptions of their rights, however, warrants further investigation. In an effort to better understand the development of students’ perceptions of school disciplinary climates amid variation in school legal environments, we identified students’ perceptions of their due process rights based on 5,490 student surveys and 86 in-depth interviews in New York, North Carolina, and California high schools. We then examine the link between students’ perceptions of their due process rights, their past experiences with school discipline, and their perceptions of school disciplinary fairness. While quantitative results reveal a negative relationship between students’ perceptions of their rights and perceptions of disciplinary fairness, our qualitative data bolster this finding and deepen our understanding of students’ perceptions, illustrating students’ complex, varied, and often vague understandings of their due process rights when faced with disciplinary sanctions. As prior work has underscored the critical relationship between students’ perceptions of their schooling experiences and educational outcomes, uncovering this negative relationship is an important step toward understanding how variation in perceptions of rights may have consequences for students’ educational outcomes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.813

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 studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.032
GPT teacher head0.332
Teacher spread0.301 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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Same venueeScholarship (California Digital Library)Same topicEducation Discipline and InequalityFrench-language works237,207