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Record W3160976478

Advocating with Humility: Improving Access of Treatment Services for Filipino Immigrant Families with Autistic Children in Alberta, Canada

2020· article· en· W3160976478 on OpenAlexaboutno aff
John Cedric Marquina

Bibliographic record

VenueNational University System Repository (National University System) · 2020
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationHumilityCultural humilityMulticulturalismPolitical sciencePsychologyCultural competencePedagogyLaw
DOInot available

Abstract

fetched live from OpenAlex

Different factors influence access to services for Filipino immigrant families with autistic children in Alberta, Canada. These include the immigration process, the immediate needs of the family as they settle down in their new environment, unfamiliarity in getting services for their children, family dynamics, cultural identity, cultural beliefs about autism, financial constraints, and other personal factors. As a result, Filipino immigrants are less likely to access healthcare services compared to other immigrant populations in North America. The use of cultural humility by mental health professionals will address the dynamic intersectionality of these factors and influence access to services for Filipino immigrant families with autistic children. Moreover, cultural humility will help clinicians learn strategies that respect Filipino immigrant families' cultural identity. In particular, the methods of reflective practice, collaborative learning, social justice, and advocacy integration are applicable. These techniques will help therapists strengthen their relationship with Filipino immigrant families, create positive changes in their lives, and ensure healthy development for their children. Therapists may use cultural humility to enhance access, utilization, and engagement of services for Filipino immigrant families with autistic children.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.237
Teacher spread0.221 · 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
Published2020
Admission routes1
Has abstractyes

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