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Record W2487472792

Treating youth agression and related problems in a social services agency

2014· book-chapter· en· W2487472792 on OpenAlexfundno aff
Stephen Ellenbogen, Robert Calame, Kim Parker, Johannes Finne, Nico Trocmé

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2014
Typebook-chapter
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
FundersRoyal Bank of CanadaUniversité de MontréalUniversité de Sherbrooke
KeywordsAgency (philosophy)CriminologyPolitical scienceSociologySocial science
DOInot available

Abstract

fetched live from OpenAlex

Family TIES (training in essential skills) is a multilevel treatment program for helping youth with anger, aggression, and interconnected problems. It is embedded within a social service centre that provides child protective and youth offender services. In this article we summarize the program’s origin and theoretical foundation, and discuss the results of a preliminary investigation. Based on the premise that youth problems emerge largely from family discord, the program involves (a) teaching prosocial and anger management skills to youth, (b) training parents to become supportive coaches for their children, and (c) enacting effective family problem solving within the context of multi-family group sessions. The intention is to replace negative family processes with constructive communication between family members, positive expectations about one another, and shared beliefs in the family’s capacity to arrive at mutually agreeable solutions to problems. As part of an internal investigation of the program, youth-report and parent-report measures of youth behaviour, youth social skills, youth and parent anger, parenting, and family functioning were administered prior to and after delivery of the program. Positive changes were found in principal measures of interest, i.e., reductions in youth aggression, rule breaking, and anger; improved parental monitoring; and fewer family functioning problems. The results provide justification for evaluating Family TIES using an experimental design.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.501
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.341
Teacher spread0.287 · 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 designQualitative
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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