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Record W4220742945 · doi:10.1177/10443894221081609

Lifespan Navigation-Building Framework for Children/Youth With Neurodisability and Their Families

2022· article· en· W4220742945 on OpenAlexafffundabout
Michèle L. Hébert, David Nicholas, Lucyna Lach, Wendy Mitchell, Jennifer Zwicker, Wenda Bradley, Sandy Litman, Emily Gardiner, Anton R. Miller

Bibliographic record

VenueFamilies in Society The Journal of Contemporary Social Services · 2022
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsUniversity of British ColumbiaAlberta Health ServicesMcGill UniversityUniversity of Calgary
FundersKids Brain Health NetworkAzrieli Foundation
KeywordsConceptualizationPublic relationsThematic analysisCitizen journalismGovernment (linguistics)Service (business)Empirical researchQualitative researchParticipatory action researchKnowledge managementSociologyPolitical scienceBusinessComputer scienceMarketingSocial science

Abstract

fetched live from OpenAlex

This study served to conceptualize neurodisability (ND) navigation-building. Capacity-building toward wide-reaching ND navigation or help-seeking service lacks empirical evidence. Researchers widely agree that a system-wide framework is absent. While research emphasizes service-level findings, other jurisdiction- and policy-level insights are lacking. Using Collective Community Impact and Participatory Action Research, government and nongovernment organizations in three Canadian regions implemented novel cross-jurisdictional initiatives to improve navigation capacity. Family-partners and other stakeholders systematically engaged in discussions. Grounded in qualitative thematic design, we sought to unveil connections between emerging themes. These themes led to stakeholders co-constructing an intersectoral navigation-building conceptualization. A framework was essential for highlighting change-levers and potential replication in other jurisdictions/landscapes. Finally, practice and policy implications compatible with an ecosystem model are presented.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.044
GPT teacher head0.364
Teacher spread0.319 · 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

Citations5
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueFamilies in Society The Journal of Contemporary Social ServicesSame topicAssistive Technology in Communication and MobilityFrench-language works237,207