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Record W2023112017 · doi:10.1007/s10897-005-0572-1

Educating Genetic Counselors in Australia: Developing an International Perspective

2005· article· en· W2023112017 on OpenAlexaboutno aff
Margaret Sahhar, Mary‐Anne Young, Leslie J. Sheffield, MaryAnne Aitken

Bibliographic record

VenueJournal of Genetic Counseling · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsGenetic counselingPerspective (graphical)Public healthHuman geneticsMedicineFamily medicineMedical educationNursingGeneticsBiologyComputer science

Abstract

fetched live from OpenAlex

The demand for genetic counseling services is increasing worldwide. This paper highlights the Australian experience of genetic counselor education and the history of the profession. The relevance of local factors, including the health care system, the education system and the small population in the evolution of the 1-year training programs are considered as an alternative model for emerging programs. The development of the education and training processes compared to that of other countries namely the United States of America (USA), the United Kingdom (UK) and Canada is discussed. The importance of international collaborations between the programs, to facilitate academic discussion and possible curriculum innovations, and to maintain professional understanding between genetic counselors is emphasized. Core genetic counseling competencies have been published for the UK and USA and an Australian set is proposed. In conclusion future directions are considered, including international issues around genetic counseling certification, reciprocity, and the potential for an Australian role in training genetic counselors in South East Asia.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.340
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations37
Published2005
Admission routes1
Has abstractyes

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