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Record W7034440949

The Successful Transitions Initiative: Youth Skills Development Programming and How At-risk High School Participants Report Impact to Academic Success and Dropout Outcomes

2019· article· en· W7034440949 on OpenAlexaboutno aff

Bibliographic record

VenueIslandScholar (University of Prince Edward Island) · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsPositive Youth DevelopmentPrideCurriculumMultitudePopularityDropout (neural networks)Life skillsIntervention (counseling)At-risk studentsSchool dropout
DOInot available

Abstract

fetched live from OpenAlex

People who fail to attain a high school education face a multitude of risk factors associated with health, employment, crime, substance abuse, and their personal lives. The Successful Transitions Initiative on Prince Edward Island, a unique program targeting youth at-risk of dropping out of high school, teaches the youth basic skills in hopes of improving their academic outcomes. Skills development programs with similar mandates and curriculum are growing in popularity across Canada. It is important that the impact of these programs be understood to ensure they are affecting the participants positively and to improve program delivery. A case study was completed to understand the impact of the Successful Transitions Initiative. Pre and post-test survey data and post intervention focus group data were analysed to measure the 2017 Successful Transitions Initiative participant-reported outcomes of the program. The participants reported improved communication skills, pride and a sense of accomplishment, higher levels of selfconfidence, self-actualization, internal locus of control, increased school engagement, and newly formed positive relationships. The Successful Transitions Initiative case study also revealed trends that support a relationship between the magnitude and the longevity of the effect. Limitations of this study unearthed recommendations for future research designs and methods.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.252
Teacher spread0.236 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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