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Solution-Focused Brief Therapy in Schools

2015· reference-entry· en· W912622035 on OpenAlexaboutno aff
Cynthia Franklin, Constanta Belciug

Bibliographic record

VenueEncyclopedia of Social Work · 2015
Typereference-entry
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSolution focused brief therapySocial workPovertyIntervention (counseling)TruancyPsychological interventionMainland ChinaPsychologyChinaPsychotherapistMedical educationMedicinePolitical scienceCriminologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract One of the most promising areas of intervention for Solution-Focused Brief Therapy (SFBT) is with children, adolescents, and teachers in school settings. SFBT was applied in schools during the beginning of the 1990s and since that time the use of SFBT in schools has grown across disciplines with reports of SFBT interventions and programs implemented in schools in the United States, Canada, Europe, Australia, South Africa, and in the provinces of Mainland China and Taiwan. The brief and flexible nature of SFBT, and its applicability to work with diverse problems, make SFBT a practical intervention approach for social workers to use in schools. SFBT has been used in schools with student behavioral and emotional issues, academic problems, social skills, and dropout prevention. SFBT addresses the pressing needs of public school students that struggle with poverty, substance use, bullying, and teen pregnancy. It can be applied in group sessions, as well as individual ones, and in teacher consultations. There is also increasing empirical support that validates its use with students and teachers. SFBT has been applied to improve academic achievement, truancy, classroom disruptions, and substance use. The history and development of SFBT in schools, basic tenets of SFBT, the techniques that are used to help people change, and the current research are covered along with the implications for the practice of social work.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.387
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.031
GPT teacher head0.306
Teacher spread0.276 · 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.

Study designNot applicable
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

Citations17
Published2015
Admission routes1
Has abstractyes

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