Bibliographic record
Abstract
Like the human mind, the human body is the medium by which we represent ourselves, whether we are patients or healthcare providers. This paper concerns the significance of understanding the existential phenomenological side of a patient’s body within healthcare. To care for a patient’s body, one needs to be aware of how the body appears to itself, to others, and in a lager environmental reality. We think and feel and observe the world with our body, especially with the brain and nervous system, but also with other dimensions of the body manifesting itself as a somatic tonus. The healthcare providers’ body does not only represent a profession, but also who they are as a person and what kind of environment they are affected by. The same applies to the patients' body. As a tool for experiencing, a tool inseparable from our very being, our physical body functions as a surface open to and in contact with the healthcare environment that surrounds it. In the modern healthcare regime, the human body is nearly always visible and under constant surveillance. In the environment of control and visibility bodies become psychologized and normalized to fit into sociocultural demands of economic adaption, social participation, and communication, which in certain situations seem hostile to the ideology of care, freedom, and humanity. We should realize that all our ethical concepts and norms, even the very notion of humanity that underwrites them, depend on social forms of life involving the ways we experience our bodies in different medical and sociocultural situations.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".