Bibliographic record
Abstract
In human lives, technology holds sway in mundane and extraordinary ways, such as in the ways we work, entertain, transport, and feed ourselves, and importantly in the ways we encounter and manage health, disease, illness, and death. A significant area of Heidegger's later work is questioning technology. Unlike many current inquiries that centre on contemporary technology's function, utility, and positive transformations, Heidegger offers a radical way of thinking about technology through developing an inquiry that uncovers technology's essence of revealing. In this article, Heidegger's thinking about technological modes of revealing in regard to bodies, health, and illness is explored. In Heidegger's view, the ordered revealing of modern technology has overshadowed other modes of revealing. This article highlights how remembering concealment and unconcealment in its many modes can be relevant to nurses and others involved in health care. Through tracing Heidegger's thinking about technology, a more critical approach to the effects and outcomes of modern technologies within health care systems can be generated.
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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.071 |
| Scholarly communication | 0.011 | 0.027 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".