Interdisciplinary research : diverse approaches in science, technology, health, and society
Bibliographic record
Abstract
Contributors. Preface. 1. Research Today (Professor Malcolm Crowe, University of Paisley). 2. Studying Complexity (Professor Ian Boyd: University of St Andrews). 3. A Sustainable Environment? A 'Lopsided View' of an Environmental Geochemist (Professor Andrew S Hursthouse, University of Paisley). 4. Use and Abuse of Statisticians (Mr Mario Hair, Statistics Consultancy Unit, University of Paisley). 5. Research in Information Systems - Mine and my Colleagues (Dr Abel Usoro, University of Paisley). 6. Hearing Lips and Seeing Voices: Illusion and Serendipity in Auditory-Visual Perception Research (Professor John MacDonald, Professor of Psychology, Division of Psychology, University of Paisley). 7. Research in Modern History (Professor Martin Myant, University of Paisley). 8. 'Scientificity' and its Alternatives: Aspects of Philosophy and Methodology within Media and Cultural Studies Research (Professor Neil Blain, University of Paisley). 9. The Truth as Personal Documentation: An Anthropological Narrative of Hospital Portering (Nigel Rapport, Concordia University of Montreal). 10. Philosophy, Nursing and the Nature of Evidence (Professor P Anne Scott, School of Nursing, Dublin City University). 11. Researching the Spiritual: Outcome or Process (Dr Harriet Mowat and Professor John Swinton, University of Paisley). 12. Using Narrative in Care and Research - the Patient's Journey (Professor John Atkinson, University of Paisley). Index.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.047 | 0.017 |
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".