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Record W3176530866 · doi:10.7202/1078514ar

Policies Matter: Closing the Reporting and Transparency Gaps in the use of Restraint, Seclusion, and Time-Out Rooms in Schools

2021· article· en· W3176530866 on OpenAlexaffvenueabout
Nadine Bartlett, Taylor Ellis

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2021
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSeclusionAccountabilityTransparency (behavior)ScrutinyDocumentationPublic relationsPolitical sciencePsychologyPublic administrationLawPsychiatry

Abstract

fetched live from OpenAlex

Information about the use of physical restraint, seclusion, and time-out rooms in Canadian schools has primarily been anecdotal (media reports and anonymous survey data) due to uneven and non-existent mandates for reporting, transparency and public accountability. The absence of clearly articulated mandates to provide written documentation and publicly available data has allowed this issue to remain obscured from public scrutiny and has severely hampered advocacy efforts for students with disabilities, who are disproportionately impacted. Building upon a prior policy analysis that investigated the policy landscape of physical restraint, seclusion, and time-out in Canadian educational jurisdictions, the current policy analysis explores an additional variable, which was not previously considered, notably the degree to which educational jurisdictions provide clear regulatory requirements to document, report, and review incidents of physical restraint, seclusion, and time-out rooms in schools. Findings indicate that inconsistent reporting requirements have created glaring gaps and loopholes in accountability mechanisms that severely disadvantage students with disabilities. Recommendations include problematizing the institutionalized structures that enable information about the use of restraint, seclusion, and time-out to be filtered and concealed, and identifying guiding principles, which are grounded in research, that can provide a framework for much needed regulatory standards relative to this issue.

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)0.116
metaresearch head score (Gemma)0.301
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1160.301
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.009
Science and technology studies0.0170.022
Scholarly communication0.0240.013
Open science0.0050.006
Research integrity0.0050.007
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 head0.089
GPT teacher head0.413
Teacher spread0.324 · 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.

Study designObservational
DomainReporting
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
Published2021
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Educational Administration and PolicySame topicHealthcare Decision-Making and RestraintsFrench-language works237,207