Bibliographic record
Abstract
Ken Ruba came to New Zealand from Canada in 1978 to teach special education courses and to work on his PhD at Massey University. His PhD was in the area of computer assisted instruction and he set up the first course on the subject ever to be offered at a New Zealand university.Over the years he has written scores of articles on special education and computers in education He has also carried put research projects and published extensively on a rangeof subjects in educational psychology and special education. Ken was instrumental in setting up the Master of Education (Special Education) degree at Massey University Following this he spent two years at the University of Waikato in the School of Education developing a new Master of Special Education degree With the establishment of the new Massey University Albany Campus he was reappointed by Massey University and subsequently took the initiative to establisha Master of Educational Psychology and a Post Graduate Diploma in Educational Psychology which leads students toward their registration as psychologists.
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".