"What's My DNA Worth, Anyway?" A Response to the Commercialization of Individuals' DNA Information
Bibliographic record
Abstract
Extensive enthusiasm surrounds the potential for human DNA information to sustain and enhance the pharmaceutical industry's profitability. Nevertheless, persons whose health makes their DNA of commercial interest are routinely expected simply to give their DNA and the information in it to pharmaceutical or genomics companies or their academic intermediaries, voluntarily and without compensation. This state of affairs is increasingly recognized as paradoxical, but it is favored by conventional bioethical opinion. Given that most DNA information is now collected for commercial purposes and is worth considerably more than is generally imagined, bioethical objections to compensation of individuals for their DNA information are inappropriate. This paper suggests approaches by which individuals and representative governments and patient interest groups can negotiate compensation. Appreciable attitudinal change is required if those individuals personally involved are to be included fairly in the commercialization of human DNA information. Ultimately, however, such change is necessary if commercial genetic research is to respect human dignity and human rights.
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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 | 0.026 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.063 | 0.047 |
| 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".