Genetic counselors with advanced skills: I. Refining a model of advanced training
Bibliographic record
Abstract
Advanced training for master's trained genetic counselors has been a topic for many years. In 2016, Baty et al. published a model of advanced training for genetic counselors that interconnects three grids: skills, paths, and positions. The purpose of this qualitative study was to assess how well this model of advanced training reflected the experiences of genetic counselors with advanced genetic counseling skills. Using purposive sampling and deductive content analysis, results of 17 interviews demonstrated that the 3-grid model of advanced genetic counseling skills, paths to attaining these skills, and positions which utilize advanced skills, described elements important for the interviewees' career development. Results suggested refinements to the model in terms of content and organization and also suggested that advanced training be conceptualized as an important element of a career lattice that includes both vertical and horizontal movement. This refined model of genetic counselor advanced training can foster profession-wide career development by stimulating new career paths and career development research.
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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) | 0.001 | 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".