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Record W1982160476 · doi:10.1375/brim.11.2.152

The Measurement of Sociomoral Reasoning in Adolescents With Traumatic Brain Injury: A Pilot Investigation

2010· article· en· W1982160476 on OpenAlexaff
Julian Dooley, Miriam H. Beauchamp, Vicki Anderson

Bibliographic record

VenueBrain Impairment · 2010
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMoral reasoningPsychologyCognitionDevelopmental psychologyClinical psychologyMoral developmentPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Abstract Moral reasoning skills are crucial for appropriate and adaptive social functioning. Impairments in moral reasoning have been associated with aggressive and violent behaviours. Traditional measures of moral reasoning may provide limited insight into daily behavioural functioning as these measures are dependent on several higher order cognitive skills and, as such, may be limited in their utility with certain clinical populations. In Study 1, new measures of sociomoral reasoning and maturity, the So-Moral and So-Mature, were described. Further, the psychometric properties of the So-Moral and So-Mature were investigated in a sample of 50 adolescents aged 11 to 19 (mean age = 14.5, SD = 2.6 years, 25 male). Preliminary support was found for the validity and reliability of both tasks. In Study 2, the clinical applicability of the So-Moral and So-Mature were examined in a sample 25 adolescents with traumatic brain injury (TBI; mean age = 13.8, SD = 2.3 years, 15 male). Response trends suggested that adolescents with TBI generated less developmentally mature responses to sociomoral dilemmas and those with more severe injuries performed most poorly. The sociomoral reasoning tasks described promote participant's emotional involvement and investment as well as being appropriate for use with clinical populations.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.403

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 studies0.0000.000
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 head0.096
GPT teacher head0.294
Teacher spread0.198 · 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 designBench or experimental
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

Citations42
Published2010
Admission routes1
Has abstractyes

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