A History of Dogs as Subjects in North American Experimental Psychological Research
Bibliographic record
Abstract
The modern resurgence in psychological experiments involving dogs follows a long and rich tradition of using dogs as experimental subjects in psychology.Except for a few exceptions (e.g., Pavlov, and Scott and Fuller), much of this research is often overlooked.We trace the history of dogs as experimental psychological subjects: The work of Darwin and Pavlov sets the stage for our focus on research emanating from North American laboratories.We end our review with the advent of the modern renaissance of dog research.This account tracks the history of psychology as a science, providing insight into psychological processes and theoretical corollaries of these processes generally, and shedding light on the behavior of dogs specifically.A rediscovery of this literature can only aid research being conducted today, including rejuvenating old questions, suggesting new ones, and highlighting useful methods for current issues.We hope through this endeavor that those working with dogs will see themselves as part of this rich tradition and that a historical perspective will help integrate dog research into a field greater than the sum of its parts.
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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 | 0.029 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".