Bibliographic record
Abstract
Abstract Genetic counselling is the process of helping people understand and adapt to the medical, psychological and familial implications of genetic contributions to disease. The majority of genetic counsellors work in clinical care settings, but a growing number work in public health and policy, educational, industry and research settings. Genetic counselling educational programmes focus on mastery of basic genetics principles, knowledge of medical genetics within a wide range of medical specialties and expertise in counselling techniques and ethical issues related to genetic conditions. Graduate education programmes were first developed in the United States, where genetic counselling is generally practised by master's prepared allied health professionals. In the past 53 years, the profession has grown to over 6000 certified genetic counsellors in the United States and Canada, with almost 7000 genetic counsellors in 28 countries worldwide. Models of genetic counselling and genetic counsellor education develop differently in different countries and health care systems. Key Concepts Genetic counselling is the process of helping people understand and adapt to the medical, psychological and familial implications of genetic contributions to disease. Genetic counsellors are allied health professionals who have graduate education in clinical genetics and the psychosocial and ethical aspects of genetic disease as well as specialised training in counselling techniques. Genetic counsellors work in many patient‐facing healthcare settings (e.g. perinatal genetics, cancer genetics, clinical genetics and subspecialty clinics) and in non‐patient‐facing settings such as public health and policy; diagnostic laboratories; research; industry settings and advocacy and other not‐for‐profit genetics groups. Genetic counsellors' job opportunities and roles are expanding in both patient‐facing and non‐patient‐facing settings. Genetic counsellors who provide direct patient care collect and assess medical information leading to a diagnosis; calculate and provide risk information; discuss options; facilitate genetic testing and provide psychosocial support and counselling to aid patients and their families adapt to conditions with a genetic component. Genetic counsellors educate clients, other medical professionals and the public about natural history, inheritance, testing, management and prevention of genetic disease. In the United States and Canada, genetic counselling has developed a strong professional identity, with a professional society, certification of genetic counsellors, accreditation of training programmes, a Code of Ethics, a professional journal, a national scope of practice, licensure, practice‐based competencies and a body of literature related to outcomes and processes of genetic counselling. Genetic counselling is a rapidly growing international profession with almost 7000 genetic counsellors in at least 28 countries.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.405 | 0.143 |
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".