Endel Tulving: An appreciation of his scientific contributions
Bibliographic record
Abstract
We review Endel Tulving's primary scientific accomplishments. The first section, by Roediger, covers the period from 1957 to 1975, during which Tulving introduced the concepts and phenomena of subjective organization, the availability and accessibility of memories, the power of retrieval cues, the recognition failure of recallable words, the encoding specificity principle, and the distinction between episodic and semantic memory. In the second section, Schacter describes Tulving's growing interest in neuropsychology, his studies of amnesic patient K.C., and his involvement in the development of the Unit for Memory Disorders at the University of Toronto. During this time, Tulving introduced the concept of mental time travel and the idea that memory for the past underlies thoughts of the future. In the third section, Craik describes Tulving's discoveries using brain-imaging techniques, first employing positron emission tomography (PET) and then functional magnetic resonance imaging (fMRI). He describes research that gave rise to Tulving's idea that encoding of memories relies on the left prefrontal cortex and retrieval of memories on the right prefrontal cortex (the HERA theory, for Hemispheric Encoding Retrieval Asymmetry). Craik also briefly discusses the status of the HERA model and other aspects of Tulving's work later in his life. We conclude by noting Tulving's impact on the authors and the field, as well as a selective review of the awards Tulving received for his research.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".