Bibliographic record
Abstract
During the last 3 years the interface between geography and nursing has provided fertile ground for research. Not only has a conceptual emphasis on space and place provided nurse researchers with a robust and subtly different way to deconstruct and articulate nursing environments, but also their studies have provided a much needed focus on certain areas of health-care, and in particular clinical practice, not currently prioritized by health geographers. We argue that, as something that is forcing fundamental re-considerations of the nature of both nursing and geography, cyberspace is a particularly important phenomenon that lies comparatively under-researched at this interface. To encourage some interest in researching nursing and cyberspace through a geographical lens, and at least to showcase a range of potentially useful and transportable concepts, we provide an overview of some of the key debates pertaining to cyberspace developed by human geographers, and make some initial and tentative connections to nursing.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.065 |
| Scholarly communication | 0.023 | 0.033 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".