Exploring discourse surrounding therapeutic enhancement of veterans and soldiers with injuries
Bibliographic record
Abstract
BACKGROUND: Human enhancement (the enhancement of the abilities of a normative person beyond the norm) of soldiers has been debated for some time. However, therapeutic enhancement of soldiers and veterans with injuries (the enhancement of the abilities of a sub-normative labeled person beyond the norm) is much less discussed. OBJECTIVE: This article discusses 1) historical examples of policies and views linked to soldiers and veterans that have been injured in the Americas, and perception of injured veterans and soldiers; 2) the science and technology of the therapeutic enhancement landscape and 3) views of veterans on therapeutic enhancements. METHODS: Three methods were used: a) historical search of policy documents; b) content analysis of the New York Times and c) online delivered exploratory non-probability survey using the Survey Monkey platform. RESULTS: Researchers found that veterans played a special role in policy developments in the United States, such as disability pension plans, and that veterans who were injured were portrayed more positively than other people with disabilities in the NYT from 1851-2010. However, within the current public discourse around the use of enhancement enabling therapeutic assistive devices, the voices of injured soldiers and veterans are not visible. CONCLUSIONS: Therapeutic enhancements, especially of injured soldiers and veterans, are an under researched area with various open ethical questions in need of more coverage.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".