Bibliographic record
Abstract
The Canadian Society for Brain, Behaviour and Cognitive Science (CSBBCS) is the face of behavioral neuroscience in Canada.With a broad outlook on experimental psychology, it appeals to students and their supervisors from across the country and beyond.While we all have much in common, there are also some obstacles to communication, not the least of which are the human/other-animal divide, and the various methods and theoretical perspectives we hold.An ecological approach connects seemingly disparate areas by opening our eyes to both causal and functional questions: we have not completely understood behavior unless we grasp its function, evolution, proximate causation and development-i.e., answers to all of Tinbergen's four questions "What is it for?How did it evolve?How does it work?How did it develop?".While none of this is news to readers of the International Journal of Comparative Psychology (IJCP), it is still not common currency in Psychology today.This is all changing.Indeed, CSBBCS awarded the Donald O. Hebb distinguished contribution award to Dr. Sara Shettleworth in 2012 for her lifetime contributions to "Cognition, Evolution and Behavior".The 2016 meeting of CSBBCS, organized by Dr. Charles Collin, included a symposium on "Categorization: Causes and Consequences" aimed at pursuing this approach and bringing together researchers who otherwise might not have had a chance to exchange ideas.Dr. Dani Brunner, editorin-chief of IJCP at the time, had suggested that a symposium might be paired with a call for papers and turned into a special issue.Here it is.
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".