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Record W2887486902 · doi:10.1080/17518423.2018.1497722

Intervention strategies in residential immersive life skills programs for youth with disabilities: a study of active ingredients and program fidelity

2018· article· en· W2887486902 on OpenAlexafffund
Gillian King, Amy C. McPherson, Shauna Kingsnorth, Jan Willem Gorter, Andrea DeFinney

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2018
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalMcMaster UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsChecklistFidelityPsychologySession (web analytics)Active listeningIntervention (counseling)Applied psychologyMedical educationDevelopmental psychologyComputer scienceMedicineCognitive psychologyCommunication

Abstract

fetched live from OpenAlex

Objective: To examine intervention strategy use in residential immersive life skills (RILS) programs.Methods: The Service Provider Strategies-Checklist was used to record the strategies used in 100 activity settings across two summers at three RILS program sites. Activity settings were categorized by activity type and session format. Relative occurrence of the strategies was examined using percentages.Results: Socially mediated strategies (listening, engaging youth) and teaching/learning techniques (verbal cues, verbal instruction) were used in over 75% of the settings. Strategy use was highly contextualized, with different strategy patterns observed for different types of activity settings.Conclusion: The findings suggest that RILS programs be characterized by their use of socially mediated strategies and teaching/learning techniques, with socially mediated and non-intrusive strategies appearing to be program hallmarks. Strategy use was aligned with the types of sessions offered, providing evidence of program fidelity and indicating that RILS programs are complex in their formats, activities, and strategy use.

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)0.001
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 score0.200
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.382
Teacher spread0.337 · 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

Citations9
Published2018
Admission routes2
Has abstractyes

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