Demographics and Employment Destinations of a New Group of Veterinary Technologists in Australia
Bibliographic record
Abstract
This article provides a descriptive analysis of the demographics and employment destinations of the first three cohorts (2003-2005) of graduates (N=69) from a program that is unique in Australia: the Bachelor of Applied Science (Veterinary Technology) at the University of Queensland. Data for this study were collected in February 2006 via e-mail, telephone, or personal communication with graduates, and from university records. Ninety-three percent (64/69) of the graduates were female. The mean age was 23 years, and 58% (40/69) had entered university directly from high school. Employment destinations were determined for 96% of the graduates (N=66). Of those, 52% (34/66) were employed in veterinary practices. Government agencies and allied animal industries accounted for 15% (10/66). Another 14% (9/66) had enrolled in further undergraduate study. Three percent (2/66) had enrolled in a research honors year or a doctor of philosophy (PhD) degree program at the School of Veterinary Science. Eight percent (5/66) were employed in wildlife parks, zoos, or universities, and the remaining 9% (6/66) were traveling overseas, seeking employment, or employed outside the field. The study revealed that graduates were employed in diverse veterinary and allied animal health occupations. There appears to be a niche for Australian veterinary technology graduates educated in a university environment that complements the role of the veterinary profession in the twenty-first century. This reflects trends emerging in other countries, most notably the United States and the United Kingdom.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".