An Environmental Scan of Health and Social System Navigation Services in an Urban Canadian Community
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".