The post-birthday world: Consequences of temporal landmarks for temporal self-appraisal and motivation.
Bibliographic record
Abstract
Much as physical landmarks help structure our representation of space, temporal landmarks such as birthdays and significant calendar dates structure our perception of time, such that people may organize or categorize their lives into "chunks" separated by these markers. Categories on the temporal landscape may vary depending on what landmarks are salient at a given time. We suggest these landmarks have implications for identity and motivation. The present research examined consequences of salient temporal landmarks for perceptions of the self across time and motivation to pursue successful future selves. Studies 1 and 2 show that temporally extended selves are perceived as less connected to, and more dissimilar from, the current self when an intervening landmark event has been made salient. Study 3 addresses the proposed mechanism, demonstrating that intervening landmarks lead people to categorize pre- and postlandmark selves into separate categories more often than when the same time period contains no salient landmarks. Finally, we examined whether landmark-induced mental contrasting of present state and future desired state could increase goal-pursuit motivation (in an effort to bridge the gap between inferior present and better future states). Studies 4-6 demonstrate that landmark-induced discrepancies between current health and hoped-for future health increased participants' motivation to exercise and increased the likelihood that they acted in line with their future-oriented goals.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".