Bibliographic record
Abstract
Episodic memory (memories of the personal past) and prospecting the future (anticipating events) are often described as mental time travel (MTT). While most use this description metaphorically, we argue that episodic memory may allow for MTT in at least some robust sense. While episodic memory experiences may not allow us to literally travel through time, they do afford genuine awareness of past-perceived events. This is in contrast to an alternative view on which episodic memory experiences present past-perceived events as mere intentional contents. Hence, episodic memory is a way of coming into experiential contact with, or being again aware of, what happened in the past. We argue that episodic memory experiences depend on a causal-informational link with the past events being remembered, and that, assuming direct realism about episodic memory experiences, this link suffices for genuine awareness. Since there is no such link in future prospection, a similar argument cannot be used to show that it also affords genuine awareness of future events. Constructivist views of memory might challenge the idea of memory as genuine awareness of remembered events. We explain how our view is consistent with both constructivist and anti-causalist conceptions of memory. There is still room for an interpretation of episodic memory as enabling genuine awareness of past events, even if it involves reconstruction.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.004 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".