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Record W4235229694 · doi:10.24124/2012/bpgub1575

Improving outcomes for special needs children and their families

2012· dissertation· en· W4235229694 on OpenAlexaff
Carmen Hamilton

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsPracticumAgency (philosophy)Special needsFace (sociological concept)PsychologySocial workMedical educationPublic relationsPedagogyMedicineSociologyPolitical scienceSocial sciencePsychiatry

Abstract

fetched live from OpenAlex

Families with special needs children and youth face barriers to accessing services and need assistance to obtain supports to live the most optimal life possible. Social workers can assist families to navigate an unfamiliar world of services to improve the outcomes for children, youth, and their families. To fulfill the requirements of this practicum I explored the needs of special needs children and their families and the best way to provide services to this population through making connections to the literature, practicum placement, and social work practice. This report includes: A description of the practicum agency, learning goals, and theoretical orientation a review of the literature, my practicum activities, and learning experiences and a discussion of implications for practice. I conclude that special needs children and their families require formal and informal services and supports to live the most optimal life possible. --Leaf ii.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
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 science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.343
Teacher spread0.315 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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