The Abstracts of the 31st Conference of the Australasian Experimental Psychology Society
Bibliographic record
Abstract
The 31st Annual Australasian Experimental Psychology Conference (EPC'04) was held at the University of Otago, the first time the conference has been held outside Australia. Approximately 180 registrants from New Zealand, Australia, USA, Canada, UK, The Netherlands, Italy, Portugal, China, and India attended the conference, making it the biggest so far. There were 166 papers presented in six parallel streams including nine specialist symposia. Topics included perception, memory, face processing, cognition, reading, neuropsychology, eye movements, attention, biological psychology, language, learning, schizophrenia, motor control, and social cognition. The keynote address, open to the public, was given by Professor Michael Corballis from University of Auckland. About 40% of the papers were presented by students. John Cass from University of New South Wales won the EPC'04 Young Scholar Award for the best student presentation. The major innovation of EPC'04 was the provision of Grants-in-Aid to assist 31 students to attend the conference. Sponsors of EPC'04 were the Department of Psychology (whose members donated time and infrastructure), the Australasian Experimental Psychology (whose members donated funds to support student Grants-in-Aid), the Assistant Vice Chancellor of the Division of Sciences (who donated the conference rooms), the School of Business (whose members donated their staff room and atrium), the Memory Research Theme (whose members supported the student helpers), the Ministry of Education (that supported the Keynote Address), and the Dunedin City Council. The success of EPC'04 was due to the hard work, the good will, and the enthusiasm of everyone involved, including the Committee Members, the student assistants (organised by Karen Tustin), John Wilden and Charlie Gilligan (technicians), Norma Bartlett (secretary), Mike Miller and William van der Vleit (computer support), and Donovan Govan (photography).
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.166 | 0.045 |
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".