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Record W3120169385 · doi:10.1002/jcop.22498

Community lives of adolescents across multiple special needs: Discrimination, community belonging, trusted people, leisure activities, and friends

2021· article· en· W3120169385 on OpenAlexaff
Jennifer E. V. Lloyd, Jennifer Baumbusch, Danjie Zou

Bibliographic record

VenueJournal of Community Psychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBelongingnessPsychologySpecial needsPopulationExploratory researchSocial psychologyMedicineSociologyPsychiatry

Abstract

fetched live from OpenAlex

We sought to gain insights into the community lives, experiences, and activities of adolescents across multiple categories of special needs. Specifically, we: explored the particular aspects of their lives adolescents felt elicited discrimination; determined whether adolescents feel a sense of community belongingness, as well as the categories of people whom adolescents approach when help is needed; and detailed the leisure activities respondents undertake and with which frequency, in addition to the quantity of friendships they have. We performed assorted descriptive analyses of the McCreary Centre Society's 2013 British Columbia Adolescent Health Survey (BCAHS) database. We found tremendous variation in the survey responses of adolescents, both within and between special needs categories, highlighting the importance of such exploratory analyses. This paper provides inductive population-based evidence to inform theories about the community lives of adolescents with special needs, as well as to guide programs and policies targeting such youth.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.003
Research integrity0.0000.001
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 head0.081
GPT teacher head0.447
Teacher spread0.366 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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