Failures to replicate hyper-retrieval-induced forgetting in arithmetic memory.
Bibliographic record
Abstract
Campbell and Phenix (2009) observed retrieval-induced forgetting (slower response time) for simple addition facts (e.g., 3 + 4) immediately following 40 retrieval-practice blocks of their multiplication counterparts (3 × 4 = ?). A subsequent single retrieval of the previously unpracticed multiplication problems, however, produced an retrieval-induced forgetting (RIF) effect about twice as large for their addition counterparts. Thus, a single retrieval of a multiplication fact appeared to produce much larger RIF of the addition counterpart than did many multiplication retrieval-practice trials. In several subsequent similar studies, however, we failed to observe this hyper-RIF effect. Here, we attempted an exact replication of the Campbell and Phenix experiment, but found no evidence of hyper-RIF. We conclude that the hyper-RIF effect reported by Campbell and Phenix is an elusive phenomenon; consequently, it cannot at this time be considered an important result in the RIF literature.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".