Re-framing writing (support): centring audience and purpose in a community nursing course
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This presentation examined the collaboration between our Learning Development team and a community nursing course. It began with the question; “Are our demands of students concerning paraphrasing and referencing reasonable?” The assignment was a formal report on a semester-long group project where students partnered with a community agency. The coordinators worried that students (and lecturers) were over emphasising referencing and the technicalities of paraphrasing, to the detriment of engagement with the community nursing process itself. Our LD team eventually realized that the problem was not one of expectations, but rather a genre-audience mismatch. Although the assignment was called a report, the emphasis on integrating scholarly sources made it more like an academic essay, and the tone and length of the report limited its practical use by most partner agencies. Over time, by emphasizing genre, audience and purpose, we have contributed to a gradual loosening of the hold on the original report format. Last year, we provided feedback on a range of digital deliverables, including infographics, videos, and mind maps, each one designed to meet the specific partner agency’s needs. Our model of providing feedback on the report during one-hour in-person meetings has also evolved into a flexible combination of synchronous and asynchronous collaboration with students. We continue to guide students towards thoughtful, transparent source use, but the conversations around referencing and paraphrasing are now more holistic. In this presentation, we’ll share how our discipline-external perspective has supported meaningful student learning about authentic (and impactful) writing for different contexts.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it