Personality and sex differences in mattering and purpose-in-life
Bibliographic record
Abstract
Abstract Mattering and purpose-in-life are key aspects of individuals’ perception of who they are and their relationships with others. However, their associations with personality, as well as sex differences within these associations, remain relatively unexplored. Three studies investigated, respectively, the correlation between mattering and purpose-in-life across sexes ( N 1 = 906), their measurement invariance by sex and associations with the Big-Five ( N 2 = 400), and with antagonistic traits ( N 3 = 178), including potential sex differences in these associations. Study 1 found lower purpose-in-life in women compared to men, but no difference in mattering. Additionally, a positive and moderate correlation between mattering and purpose-in-life was observed, but no sex differences. Study 2 found higher factor covariance in men than women. Moreover, it showed that conscientiousness positively predicts mattering and purpose-in-life, neuroticism negatively predicts both, and agreeableness positively predicts purpose-in-life. Study 3 showed that primary and secondary psychopathy negatively predict mattering, grandiose narcissism positively predicts mattering and purpose-in-life, and secondary psychopathy negatively predicts purpose-in-life, in all cases showing no sex differences. These results highlight the importance of mattering and purpose-in-life in personality research and intervention, offering insights for personality development by addressing dysfunctional perceptions and fostering personal and professional growth across various applied settings. For instance, in counseling, leveraging mattering and purpose-in-life could help clients strengthen their resilience and coping skills. In educational settings, mattering and purpose-in-life could support learners’ self-efficacy and improve educational outcomes. In organizational settings, they could drive change by enhancing individuals’ confidence, productivity, and leadership.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".