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Record W2585380164 · doi:10.1177/2377960816689566

An Environmental Scan of Health and Social System Navigation Services in an Urban Canadian Community

2017· article· en· W2585380164 on OpenAlexaffabout
Nancy Carter, Ruta Valaitis, Janice Feather, Laura Cleghorn, Annie Lam

Bibliographic record

VenueSAGE Open Nursing · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsCLARITYSocial workMental healthPublic relationsBureaucracyService providerNursingBusinessService (business)PsychologyMedicinePolitical scienceMarketing

Abstract

fetched live from OpenAlex

Systems navigation services provided by a designated provider or team have the potential to address health and social disparities. We conducted an environmental scan of navigation activities in a large urban Canadian community to identify and describe: service providers who engage in systems navigation; the clients who require systems navigation support and the issues they face; activities involved; and barriers and facilitators in providing systems navigation support to clients. Using an online survey and convenience sampling, we recruited individuals who self-identified as community navigators or practiced systems navigation activities as part of their role. The majority of respondents ( n = 145) were social workers, social services workers, or nurses. Clients of navigators struggled with mental health or addictions issues, disabilities, chronic diseases, and history of trauma or abuse. The most frequently reported activities of navigators were building professional relationships, managing paperwork, and communicating with relevant agencies or organizations. Barriers to navigation were time available in the work day, difficulty partnering due to bureaucratic structures, differing philosophies and ways of working, and a lack of central information repository in the community. Facilitators were a client-centered organization, the availability of multiple community resources in the region, and organizational support. Participants struggled with client waitlists, system issues such as lack of resources and interagency collaboration, and role clarity.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.001
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 head0.415
GPT teacher head0.637
Teacher spread0.222 · 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

Citations13
Published2017
Admission routes2
Has abstractyes

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