RESEARCH ARTICLE Open Access Challenges to immunization: the experiences of
Bibliographic record
Abstract
Background: Homelessness is a critical social issue, both a product of, and contributing to, poor mental and physical health. Over 150,000 young Canadians live on the streets. Homeless youth experience a high incidence of infectious diseases, many of which are vaccine preventable. Early departure from school and limited access to public health services makes them a particularly vulnerable high-risk group. This study explores challenges to obtaining essential vaccines experienced by homeless youth. Methods: A qualitative research study to explore knowledge, attitudes, beliefs, and experiences surrounding immunization of hard-to-reach homeless youth was designed. Participants were recruited for focus groups from Phoenix House and Shelter, a non-profit, community-based organization assisting homeless youth in Halifax, Nova Scotia, Canada. An experienced facilitator guided the recorded discussions. Transcripts of audiotapes were analyzed using a constant comparative method until data revealed a set of exemplars and themes that best captured participants ’ knowledge, attitudes, beliefs and experiences surrounding immunization and infectious diseases. Results: Important themes emerged from our analysis. Considerable variability in knowledge about immunization and vaccine preventable diseases was found. The homeless youth in the study had limited awareness of meningitis in contrast to a greater knowledge about sexually transmitted infections and influenza, gained during the H1N1/09 public health campaign. They recognized their poverty as a risk for contracting infectious diseases, along with their
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".