Critical ethnography of outreach nurses– perceptions of the clinical issues associated with social disaffiliation and stigma
Bibliographic record
Abstract
AIMS: The aim of this study was to gain a better understanding of how nurses experience their practice with homeless people. More specifically, we wanted to consider the role as it is practised and certain clinical characteristics associated with social disaffiliation and stigma. BACKGROUND: Previous research has shown the need to implement adapted nursing interventions to address the problems homeless people encounter in obtaining health services. According to the literature, such interventions have positive health outcomes for homeless people, who exhibit complex health needs. DESIGN: We chose critical ethnography as our research method. METHOD: Semi-structured interviews were conducted with 12 nurses who work with people experiencing homelessness in Eastern Canada. They were selected using the convenience sampling method. Recruitment was conducted between June-October 2019. FINDINGS: Four categories emerged from the qualitative analysis of the data: (1) the professional role and identity of nurses; (2) the social function of outreach nursing; (3) clinical realities; and (4) disaffiliation and stigmatization. In this article, we will present the findings associated with the fourth category. CONCLUSION: Nursing practice with this population is conducted in non-traditional settings such as shelters, community groups, camps, and the street. Nurses must be able to gain acceptance in these environments in order to forge trusting relationships with disaffiliated and stigmatized patients. Our analysis of the data also indicates that nurses who care for homeless people may be subject to stigma by association or "courtesy stigma." IMPACT: The results of this critical ethnography are useful in that they highlight the clinical interventions and health policies best suited to a highly marginalized clientele that is poorly served by traditional health services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".