Moving beyond the individual: Occupational therapists' multi-layered work with communities
Bibliographic record
Abstract
Introduction Although working with communities using community-centred approaches like community development has been identified as an important occupational therapy domain of practice, occupational therapists continue to struggle to clarify their roles and processes in this area of practice. From a study that aimed to describe the practice process of occupational therapists working in community development, this article presents key findings regarding how occupational therapists described their work with individuals and communities, providing a conceptualization of how to situate their work with individuals within a broad community context. Method Using interpretive description, individual interviews and focus group discussions were conducted via telephone with 12 occupational therapists from across Canada between February 2014 and March 2015. Results There was some uncertainty amongst participants regarding the definition of community development. Four layers of community-centred practice were inductively derived from the data: individual, group, community of interest, and systems. The latter two touch on community development. Conclusion The conceptualization that emerged from this study can assist occupational therapists in reflecting on current practice and furthering an appreciation of how their work with individuals can include a community focus, responding to calls within the profession to look beyond the individual.
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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.028 | 0.033 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.003 | 0.029 |
| Research integrity | 0.004 | 0.004 |
| 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".