Multiple Lenses: Rural Landscape through the Eyes of Nurse Preceptors and Students
Bibliographic record
Abstract
In a recent photovoice study, fourth year nursing students and their rural nurse preceptors provided us with photographs and commentary documenting their everyday, lived realities, from which we constructed a narrative of preceptorship in the rural nursing context. We found that rural nursing integrates professional and community values, and that landscape mediates this integration in four ways: travel, occupationalism, historicity, and symbolic projection. Rural preceptorships introduce nursing students to dichotomous perceptions of landscape, derived from rural nurses' multiple roles and the competing scripts of official policy versus community bonds. Disseminated in media-rich formats such as exhibitions, photo-essays and online resources, these findings amount to a compelling message to prospective rural nurses, educators, and policymakers: rural nursing is a specialty, too long marginalized, with its own unique challenges and rewards. Keywords: landscape, rural, nursing, preceptorship, Gemeinschaft, photovoice
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".