An exploratory study of the experiences of social workers who are employed in nurse practitioner-led clinics in the province of Ontario
Bibliographic record
Abstract
This study explored social workers’ experiences working in primary health care—specifically, those employed in Nurse Practitioner-Led Clinics (NPLC). This qualitative study utilized a sample of nine social workers employed in Ontario. Data were analyzed using a thematic analysis. Results revealed two thematic clusters pertaining to the social work role and the organizational/structural aspects of the role. Subthemes of the first cluster identified (1) the social work role as multi-faceted and hard to define, (2) issues of poverty and (3) the lack of understanding of the social work role by other professionals, including the importance of positive collegial relationships. Subthemes of the second cluster identified (1) a lack of supervision and the importance to self-care, (2) working in isolation as a challenge, and (3) conflicting models including subthemes on professional hierarchy and pay disparities. Results may help to define the role of social workers who are employed in NPLCs as well as the challenges they may encounter. This research offers a vision of how social work can make a difference within the new era of primary health care aimed at developing health care systems more suited to the needs of individuals, families and communities
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".