Bibliographic record
Abstract
BACKGROUND: The culmination of the Human Genome Project in the early 2000s came wreathed in promises of a revolution in medicine and healthcare. The ensuing quarter century has seen remarkable growth in genomic medicine, as well as notable shifts in the promissory rhetoric that accompanies it. METHODS: This essay draws on a contextualist close reading of scientific and policy literature published from the 1990s to the present, using thematic and narrative analysis informed by perspectives from the sociology of expectations, to examine the role of different kinds of promissory claims in shaping the development of genomic medicine in the UK, and particularly England, over that period. RESULTS: Early promises about the medical benefits that will follow from the development of genomic medicine have been scaled back and refocused as the possibilities and limitations of genomic technologies have become apparent; while investment has shifted from basic discovery resources aimed at elucidating the genetics of common disorders to clinical facilities focused on the genomics of rare diseases and cancer. Research in these areas has delivered a range of highly-publicised diagnostic and therapeutic innovations, but so far the benefits to patients have generally been modest or confined to relatively small populations, and come at a high cost, both financial and human. Meanwhile, a rather different set of promises, focused on economic growth through biomedical innovation, has been instrumental in shaping how the field of genomic medicine has developed, especially within the National Health Service. One consequence has been a blurring of the distinction between medical care and biomedical research, with genomic medicine patients and their data increasingly being reframed as an economic resource for purposes of commercially-driven innovation. CONCLUSION: In this context, efforts to persuade patients of the personal or public value of research participation, and especially proposals to abandon the principle of clinical non-directiveness in genomic healthcare, raise uncomfortable questions about just whose interests genomic medicine, as currently constituted, is best designed to serve.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".