South Australia's First Family Therapist — Jeff Gerrard Remembers: An Interview
Bibliographic record
Abstract
Jeff Gerrard can claim the distinction of being the first family therapist in South Australia. Early on in his career as a psychiatrist he explored the growing field of psychotherapy overseas and observed, studied, and trained with some of the historical greats in the area. When he returned to South Australia in the early 70s, it seems to have been a natural step for him to begin practising family therapy and training other health professionals in the theory and practice of family therapy. The early training that Jeff led at the South Australian Children's Hospital enabled a cooperation between a number of early family therapists, such as Michael White and Anne Sved Williams, to train the first cohort of people who would later go on to become significant contributors to the family therapy field in Australia. In this interview, Lorraine Read invites Jeff to explore his early contributions to the field and to discuss the training and supervision experiences which were/are important in his development as a family therapist.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".