The missing self in time: Duration reproductions diverge when using the “self” as a reference point
Bibliographic record
Abstract
In order to act in the world — to be in the right place at the right time — visual processing must keep track of time. Psychological time though is malleable, with the same duration seeming longer or shorter, depending on external factors (e.g., how many events occurred) or internal processes (e.g., speed of information processing). But we do not only passively perceive time; we can also make things go faster or slower depending on whether we wait and let time pass, or move things along ourselves. This agency, or the role of the “self” in relation to time, has been often isolated through the following question: “If your Wednesday meeting is moved forward by two days, when is the new meeting?” If you are *moving* toward the meeting (i.e., “ego-moving”), the answer is Friday. If you are *waiting* for the meeting to approach (i.e., “ego-stationary”), it’s Monday. Here we ask whether and how these self-time perspectives change temporal experience. Observers saw an event — a disc flash on a screen. As in typical duration experiments, they reproduced time intervals (i.e., the time elapsed between the start of the trial and the event) via button press. Critically, they also reproduced intervals with their “self” as the reference point (i.e., the time elapsed between now [where you are in time] and the past event). In a large-scale study, ego-moving observers (who reported “Friday”) reproduced shorter durations between themselves and the past event, than did ego-stationary observers (who reported “Monday”) — while no difference was observed for reproductions of intervals between events independent of the “self.” Thus, ego-moving people may be more “ready to act,” so past events are represented as having occurred more recently in time — perhaps because these are still deemed relevant for impending future action.
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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 | 0.002 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".