Las mejoras terapéuticas y la opinión de los educadores de rehabilitación
Bibliographic record
Abstract
so far, the meaning of health and therefore treatment and rehabilitation is benchmarked\nto the normal or species typical body. Therapeutic interventions increasingly have the\npotential to generate beyond the �normal� bodily abilities (therapeutic enhancements) The\nfield of rehabilitation, the desire for certain especially beyond species-typical body abilities and\nthe direction and governance of science and technology are becoming increasingly interrelated.\nHow we judge and deal with bodily abilities, or the lack of them, among others influences\nthe direction and governance of science and technology processes, products and\nresearch and development and influence the meaning and scope of health and rehabilitation,\nthe identity and job description of health and rehabilitation professionals, the desires of health\nand rehabilitation clients. This paper presents the results of an exploratory, non-probability\nsurvey of National council of rehabilitation educators (UsA) members seeking their views on\nissues of bodily enhancement and their impact on health and rehabilitation professions. The\nmajority surveyed perceived human enhancements beyond the �normal� and the attached\nchanges as unavoidable. The results indicate that it is high time that the enhancement discourse\nmoves outside the ethics realm and that impact analysis of beyond the normal enhancement\nis performed that includes so far mostly invisible health and rehabilitation\nprofessionals, their clients and disability policy scholars.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".