On Constructing a Parody and Then Knocking It Down: A Reaction to Kerr and Blais
Bibliographic record
Abstract
Kerr and Blais’ (2000) paper is frequently ambiguous, incoherent, and severely misrepresents the work of Bouffard, Strean and Davis (1998). Kerr and Blais have committed the logical fallacy of attacking a straw man, which is to misrepresent an opponent’s argument presumably for the purpose of making its attack easier. Although they indicate their desire to proceed without reference to ontological and epistemological assumptions, they implicitly submit the contentious statement that eclecticism is a philosophy that has been accepted by movement skill acquisition researchers. They also endorse eclecticism as a philosophy. In this reaction, I question the validity of numerous statements made by Kerr and Blais and elaborate on some points we made in 1998. I conclude that Kerr and Blais’ paper is a parody of Bouffard, Strean and Davis’ work, which is unlikely to advance our understanding, and submit that the study of research assumptions is an essential part of genuine inquiry.
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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 | 0.056 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.077 |
| Scholarly communication | 0.018 | 0.031 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.026 | 0.060 |
| Insufficient payload (model declined to judge) | 0.004 | 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".