Goals and everyday problem solving: Manipulating goal preferences in young and older adults.
Bibliographic record
Abstract
In the present study, we examined the link between goal and problem-solving strategy preferences in 130 young and older adults using hypothetical family problem vignettes. At baseline, young adults preferred autonomy goals, whereas older adults preferred generative goals. Imagining an expanded future time perspective led older adults to show preferences for autonomy goals similar to those observed in young adults but did not eliminate age differences in generative goals. Autonomy goals were associated with more self-focused instrumental problem solving, whereas generative goals were related to more other-focused instrumental problem solving in the no-instruction and instruction conditions. Older adults were better at matching their strategies to their goals than young adults were. This suggests that older adults may become better at selecting their strategies in accordance with their goals. Our findings speak to a contextual approach to everyday problem solving by showing that goals are associated with the selection of problem-solving strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".