Age Excuses: Conversational Management of Memory Failures in Older Adults
Bibliographic record
Abstract
The social consequences of appealing to age to excuse memory failure were examined in 2 vignette-based studies. In Study 1, 75 older (M = 72 years) and 78 young (M = 22 years) adults evaluated forgetful older targets in their 70s who used their age, lack of ability, lack of effort, or the situation to explain forgetting. In Study 2, 105 older (M = 72 years) and 105 young participants (M = 19 years) evaluated forgetful targets with no specific age given in 4 excuse conditions (age, ability, situation, and no excuse). In support of the prediction of positive consequences, age excuses were rated as more believable than situation in both studies and more believable and socially fluent than effort in Study 1. In support of predictions of negative consequences, both groups in Study 2 rated target persons who used an age excuse to be much older than their peers and, along with ability excuse users, as eliciting more worry and frustration than the others. Moreover, young adults showed additional sensitivity to the negative aspects of age excuses in terms of worry and frustration in Study 1 and anticipated repeat forgetting in Study 2. These results suggest that although age excuses may relieve socially awkward situations, this strategy reinforces negative age stereotyping of the older forgetter.
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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 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".