Bibliographic record
Abstract
The concept of change simply entails the totality of ways in which a particular entity has grown better and grown worse. Five studies suggest that this is not how people actually understand it for themselves. Rather, when asked to assess how they have "changed" over time, people bring to mind only how they have improved and neglect other trajectories (e.g., decline) that they have also experienced; global change is specifically translated as directional change for the better. This tendency emerged across many populations, time frames, measures, and methodologies (Studies 1-3), and led to important downstream effects: people who reflected on "change" from their pasts experienced enhanced mood, meaning, and satisfaction in their presents, precisely because they had assumed to only think about personal improvement (Study 4). A final study shed light on mechanisms: people evaluated the word change in a speeded response task as more positive when they were instructed to interpret the word in relation to themselves versus a friend, while no differences emerged between conditions for nonchange control words (Study 5). This suggests that the basic pattern across studies stems (at least partly) from traditional self-enhancement motives-our own change spontaneously brings to mind only the ways in which we have improved, whereas change in someone else is not so immediately and uniformly associated with improvement. Taken together, these findings reveal novel insights into the content and consequences of change perception, and they more broadly highlight unforeseen biases in when and why people might subjectively (mis)interpret otherwise objective constructs. (PsycINFO Database Record
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.022 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".