Reflections on a decade in the life of the Australasian Evaluation Society: 1990-1999
Bibliographic record
Abstract
The 2003 AES Conference 1 was the 21st birthday of conferences held by a group of evaluators who after a few such efforts organised themselves more formally in 1996 to become the AES, which was officially registered in Victoria in 1987. Ours was the third such regional professional society of evaluators, after the Canadian Evaluation Society (CES) started in 1981 and the American Evaluation Association (AEA) formed in 1986, as the consolidation of two earlier evaluation associations: the Evaluation Network and the Evaluation Research Society. This article is not a history of the AES. It lacks the academic rigour and research. It particularly overlooks much of the activity of the regions which are really the heart of the Society. It reflects my experiences, my perceptions, and my analysis over the ten years when I was most actively involved in the Society. Despite these deficiencies or potential biases, I hope it provides an insight into what goes into making a professional society as effective and highly regarded as the AES is, despite having had its share of trials along the way.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.069 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.026 | 0.020 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.018 | 0.027 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".