ADDRESSING SERVICE ACCESS BARRIERS FOR HOMELESS YOUTH: A CALL FOR COLLABORATION
Bibliographic record
Abstract
Homeless youth are among the most vulnerable individuals in North American society. The day-to-day stressors they face while living on the streets pose a great threat to their mental and physical health. A number of barriers that youth face in accessing care have been identified in the literature. This discussion article highlights work that has been done to apply geographic theory to issues of service access among homeless youth. To date, most such work has been theoretical in nature, with collaborations between geographers and homeless youth researchers to make applied recommendations for the location of services. Urban geographers and homeless youth researchers are implored to collaborate in order to make recommendations that will increase the access to service, particularly for rural homeless youth.
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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 | 0.133 | 0.138 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.031 | 0.034 |
| Open science | 0.012 | 0.055 |
| Research integrity | 0.027 | 0.049 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".