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Record W2096155683 · doi:10.1002/bsl.737

Short‐Term Assessment of Risk and Treatability (START): the case for a new structured professional judgment scheme

2006· article· en· W2096155683 on OpenAlexaff
Christopher D. Webster, Tonia L. Nicholls, Mary‐Lou Martin, Sarah L. Desmarais, Johann Brink

Bibliographic record

VenueBehavioral Sciences & the Law · 2006
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsBC Mental Health & Substance Use ServicesSt. Joseph’s Healthcare HamiltonSimon Fraser University
Fundersnot available
KeywordsRisk assessmentRisk managementHarmNeglectBridge (graph theory)PsychologyRisk analysis (engineering)Applied psychologyComputer scienceMedicinePsychiatryComputer securitySocial psychologyBusiness

Abstract

fetched live from OpenAlex

The Short-Term Assessment of Risk and Treatability (START) is a new structured professional judgment scheme intended to inform multiple risk domains relevant to everyday psychiatric clinical practice (e.g. risk to others, suicide, self-harm, self-neglect, substance abuse, unauthorized leave, and victimization). The article describes the processes involved in establishing an interdisciplinary approach to risk assessment and management. The authors present a review of the rationale for START, including the value of dynamic variables, the importance of strengths, and the extent to which clinicians must be attentive to multiple risk domains, reflecting theoretical and scientific evidence of the overlap among risks. Using the development, validation, and implementation of START as an example, the authors describe the processes by which other researchers, clinicians, and administrators could adapt existing assessment schemes or create new ones to bridge some remaining gaps in the risk assessment and management continuum.

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)0.000
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 score0.309
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.071
GPT teacher head0.411
Teacher spread0.340 · 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

Citations137
Published2006
Admission routes1
Has abstractyes

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