Bibliographic record
Abstract
In a previous study, we found the family of personality traits known as conscientiousness to be associated in cross-sectional analyses with both lifetime earnings and wealth. In this study, we used data from an Internet survey of HRS respondents in the second quarter of 2009 to test whether conscientiousness and other Big Five factors prospectively predicted responses to the financial crisis of 2008/09. In addition, to improve the targeting and design of behavioral interventions for “at-risk” individuals, we examined two specific facets of conscientiousness (i.e., self-control and perseverance) that may be more highly related to these economic outcomes than other facets. Finally, we used data from the Consumption and Activities Mail Survey (CAMS) to examine whether personality is related to the proportion of income saved vs. spent. Missing data precluded sufficiently powerful prospective analyses of personality and responses to the financial crisis. Likewise, data on self-control and perseverance from the 2010 experimental module were not sufficient at the time of final reporting to come to definitive conclusions about how these facets relate to economic outcomes. We did find that conscientious adults save more and spend less of their incomes, whereas adults who are higher in openness to experience (e.g., adventurous, sophisticated) save less and spend more of their income. The robust associations between conscientiousness and economic outcomes suggests further investigation of interventions that improve conscientiousness as well as policies that specifically target less conscientious individuals (e.g., default choices for retirement savings).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".