Encoding specificity revisited: The role of semantics.
Bibliographic record
Abstract
Three experiments examined the effects of semantic characteristics of word pairs on memory using the encoding specificity paradigm. The paradigm involved four phases: (a) an encoding phase to relate cues and targets, (b) a phase in which words were generated to new cues, (c) a phase for recognition of generated targets, and (d) a cued-recall phase using the original encoding cues. Encoding pairs were classified a priori as either semantically similar (e.g., alluring-PRETTY), semantically contrasting (e.g., drab-PRETTY), or semantically unrelated (e.g., sore-PRETTY). Generation pairs were classified a priori as either semantically similar (e.g., beautiful-PRETTY) or semantically contrasting (e.g., ugly-PRETTY). For recall, the results showed that both the semantic relations between the encoding cue and target and the reprovision of the encoding cue at retrieval were important factors. In the case of recognition, however, both the semantic congruence between the encoding and generation contexts and the amount of semantic elaboration provided by the encoding context were important factors.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".