Preparing the genetic counseling workforce for the future in Australasia
Bibliographic record
Abstract
Current genetic counseling students will graduate into a workforce involving more opportunities, diversity, and uncertainty than any previous generation. Preparing the future genetic counseling workforce is a dynamic challenge, both for the profession and for educators. The dominance of the medical model in the state funded Australian healthcare system creates a power imbalance between doctors and other health professionals. As a result, professional regulation to protect the public from harm in line with the United States, the UK, and Canada only became mandatory in 2019. Professional regulation has the additional benefit of enhancing professional standing and autonomy, enabling genetic counselors to help shape the future of genetic health care in Australia and New Zealand. Within this rapidly evolving environment, we are establishing a new Masters' program and building a discipline of genetic counseling, working alongside other allied health professionals. Our program involves synchronous and asynchronous learning, greater accessibility, flexibility and, as we have learned in 2020, reduction in disruption during a global pandemic. In this program, we foreground the inherent knowledge, skills, and values of genetic counseling, shifting the focus from provision of genetic and genomic tests, to educating competent, person-centered, research enabled and culturally safe genetic counselors. As educators, we have a responsibility to prepare students to embrace the uncertainties, challenges, and potential of the genomic era, to seize the many possibilities that lie ahead, and to expand their thinking and vision. We ask our students to be courageous, to step into a deep exploration of their own identity, beliefs, understanding, and experiences of oppression, power, and privilege. We are pushing boundaries, and challenging ourselves and our students to remain always open to possibilities. Equipping students with open eyes and listening ears may be the single most important thing we can do to prepare the genetic counseling workforce of the future to provide the best possible care.
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 | 0.001 | 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 | 0.001 |
| 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".