The Experience of Quarantine for Individuals Affected by SARS in Toronto
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to explore the experience of home quarantine during the severe acute respiratory syndrome (SARS) outbreak in Toronto in 2003. DESIGN: Qualitative descriptive design. SAMPLE: Stratified random sampling techniques were used to generate a list of potential participants, who varied in terms of gender and closeness of exposure to someone with suspected SARS (contact level). Twenty-one individuals participated in the study. MEASUREMENTS: All interviews were audiotaped and followed a semistructured interview guide. Participants were invited to describe their experience of quarantine in detail including their advice for Public Health. RESULTS: The experience followed a trajectory of stages beginning before quarantine and ending after quarantine. Despite individual differences, common themes of uncertainty, isolation, and coping intersected the data. CONCLUSIONS: Public Health has a dual role of monitoring compliance and providing support to people in quarantine. This study has implications for public health policy and practice in planning for future public health emergencies in terms of the information and the resources required to mount an effective response.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".