Bibliographic record
Abstract
A. Introduction The last few years have seen a rapid growth in the discovery of genes associated with hereditary disease or susceptibility, and an accompanying rise in the number of genetic tests becoming available. While most Canadians likely still access genetic testing through the public system, there is also a small developing private market. As more tests become available for conditions of greater general incidence, e.g., heart disease or the common cancers, there is every likelihood that the market will expand. [1] Genetic testing will provide information about individual risk for disease that may permit people to make lifestyle changes to reduce risk, make career planning decisions, or take prophylactic measures, and for those already affected, may allow for individualized therapy. [2] However, private provision may lead to premature access to unproven technologies, while marketing might minimize the uncertainties associated with testing, [3] support a reductionist view of disease and disability, [4] and inflate public anxiety to increase demand. [5] A private market also has serious implications for the Canadian public health care system. [6] Private companies will profit from overhead services without contributing to funding or development, [7] draw experienced professionals from the public to the private sector thereby reducing quality and lengthening waitlists, and increase demand for counselling and medical treatments. Despite these concerns, we currently do not have good mechanisms for controlling the development of a private market. More generally, we also lack good criteria for determining what health care services should or should not receive public funding -- the determination of health care funding is the result of an ad hoc rather than a rational decision making process. In 1999, a small interdisciplinary group of academics, clinicians, business representatives and a member of the public met to discuss the role of privately financed genetic testing in Canada. Out of this workshop was developed a paper by Caulfield, Burgess, Williams-Jones, et al., [8] that outlined an analytic framework of six thresholds to help support more rationalized decision making in the funding of genetic services. The first four thresholds determine whether anyone should receive the service: whether the test morally acceptable; whether it identifies a genetic factor; whether the test useful; and whether the test harmful. The last two thresholds consider whether the service should be financed with public monies or be available for private purchase. The goal here is to provide a summary of the larger paper that highlights its key points and recommendations. B. Thresholds 1-4: Which Tests are Acceptable? At any point in the development of a genetic test, we may decide as a society that the goals or consequences are morally objectionable and thus restricted access or prohibition of the test is warranted. We must also consider the adverse implications, for example, on potentially useful research or on economic development. This first threshold evokes questions of which values will be considered relevant, and how and by whom they will be expressed. What is the commercial influence on the way economic, technology and public policy are developed? Is public input valued only if it is educated about the technical aspects of genetic testing? Adequately addressing these questions will require further research and development of effective public participation mechanisms. It should also be noted that regardless of whether a particular genetic test is prohibited locally, Canadians can access testing through international sources.[9] But this does not eliminate the value of government regulation prohibiting specific tes ts. Such a stance can be an important statement of national values that can strongly influence consumer preferences. Genetic tests should meet some minimum standard of efficacy, such that a test at least detects what it claims to detect. …
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".