Where’s the Disconnect? Exploring Pathways to Healthcare Coordinated for Youth Experiencing Homelessness in Toronto, Canada, Using Grounded Theory Methodology
Bibliographic record
Abstract
About 900 youth experiencing homelessness (YEH) reside at an emergency youth shelter (EYS) in Toronto on any given night. Several EYSs offer access to healthcare based on youths' needs, including access to primary care, and mental health and addictions support. However, youth also require healthcare from the broader health system, which is often challenging to navigate and access. Currently, little is known about healthcare coordination efforts between the EYS and health systems for YEH. Using grounded theory methodology, we interviewed 24 stakeholders and concurrently analyzed and compared data to explore pathways to healthcare coordinated for youth who reside at an EYS in Toronto. We also investigated fundamental parts (i.e., norms, resources, regulations, and operations) within the EYS and health systems that influence these pathways to healthcare using thematic analysis. A significant healthcare coordination gap was found between these two systems, typically when youth experience crises, often resulting in a recurring loop of transition and discharge between EYSs and hospitals. Several parts within each system act interdependently in hindering adequate healthcare coordination between the EYS and health systems. Incorporating training for system staff on how to effectively coordinate healthcare and work with homeless populations who have complex health needs, and rethinking information-sharing policies within circles of care are examples of how system parts can be targeted to improve healthcare coordination for YEH. Establishing multidisciplinary healthcare teams specialized to serve the complex needs of YEH may also improve healthcare coordination between systems, and access and quality of healthcare for this population.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".