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Record W2288946008 · doi:10.1080/02673843.2016.1152986

Examining the importance of supporting youth’s basic needs in one youth leadership programme: a case study exploring programme quality

2016· article· en· W2288946008 on OpenAlexaff
Corliss Bean, Meghan Harlow, Tanya Forneris

Bibliographic record

VenueInternational Journal of Adolescence and Youth · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsYork UniversityUniversity of Ottawa
Fundersnot available
KeywordsPsychologyQuality (philosophy)Positive Youth DevelopmentApplied psychologyMedical educationDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

Researchers outline the importance of understanding features that enhance quality within youth programmes. One feature is youth’s basic psychological needs support. The purpose of this study was to examine if differences existed between two leaders in delivery of one youth leadership programme related to programme quality and needs support. A mixed-methods approach was employed. Programme quality was assessed quantitatively from researchers' observations. Youth self-reported on needs support and participated in semi-structured interviews. Results indicated significant differences on programme quality with Leader 1 rating higher on safe and supportive environment than Leader 2. Youth perceived Leader 1 as more effective than Leader 2 in providing a psychologically safe environment and fostering needs support. Implications and future directions are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.003
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 head0.425
GPT teacher head0.380
Teacher spread0.045 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations13
Published2016
Admission routes1
Has abstractyes

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