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Record W4230337754 · doi:10.24124/2017/1389

Identifying at-risk youth: strategies to help them succeed

2017· dissertation· en· W4230337754 on OpenAlexaffabout
Marie Peters

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsAdventureLiteracyIntervention (counseling)PsychologyPedagogyOrder (exchange)At-risk studentsMathematics educationComputer science

Abstract

fetched live from OpenAlex

Approximately 30-40% of Canadian children are deemed to be at risk of not completing high school and 1.2 million or 27.6% of Canadian children under the age of 11 can be considered vulnerable to emotional, behavioural, social, or academic problems. Through the use of unobtrusive research under a qualitative research paradigm, a democratic approach to education focusing on empowering members of the teaching community and students has been done. This research narrows the gap between traditional education practices and explores new ways of instruction in order to create a healthy learning environment where students are able to feel excited and empowered through their learning. This manual encourages educators to try, adapt, and adopt new methodologies in their teaching repertoire. Intervention strategies include physical literacy, adventure-based learning, strengths-based approach, and social justice.

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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0130.003
Scholarly communication0.0080.006
Open science0.0030.013
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0080.003

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 head0.082
GPT teacher head0.369
Teacher spread0.286 · 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 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
Published2017
Admission routes2
Has abstractyes

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