Bibliographic record
Abstract
This commentary focuses on the robustness of the Kamin blocking effect (KBE) that Maes et al., based upon 15 failures to replicate, have questioned. This challenge to KBE robustness has not gone unaddressed. Soto outlined conceptual as well as methodological issues that cast doubt on the validity of the Maes et al. critique. Despite recognition of certain interpretive issues, Maes et al. have reaffirmed that their failures to replicate are meaningful and call out for further parametric scrutiny of KBE. Faced with such marked differences of opinion with regard to KBE robustness, the present commentary highlights certain methodological features that may have contributed to the Maes et al. failures to replicate: (a) Roles of stimulus salience and independence, (b) Multiple test trials, and (c) Reliance on a single control procedure. It is suggested that the existence of such methodological issues renders it fallacious to argue that the Maes et al. findings represent a true failure to replicate KBE. Instead, the present formulation contends that Maes et al. engaged in a strawman argument in which they have found fault with a distorted version of KBE rather than KBE itself. Although employing variations of paradigms that had earlier been seen to generate KBE, the presence of multiple methodological shortcomings was such as to effectively mask observance of KBE. In affirmation of the Soto's critique, the replication failure reported by Maes et al. is thus seen as unsurprising. Accordingly, the Maes et al. proposal to remove KBE as a "touchstone for our theories of elementary learning" is argued to be unwarranted. In the face of this protracted dispute, the positing of a strawman argument serves to further cast doubt upon the import of the Maes et al. replication failure, and consequently, to reaffirm KBE as a core phenomenon in the learning domain.
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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 | 0.076 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 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".