Neuroticism versus emotionality as mediators of the negative relationship between materialism and well-being
Bibliographic record
Abstract
The purpose of the study was to investigate the relationship between, neuroticism, emotionality well-being and materialism. A series of mediation analyses were conducted with data obtained from a set of questionnaires completed by University students. The results indicated that neuroticism and emotionality were mediators in the well-being-materialism relationship. However, this relationship is dependent upon whether neuroticism or emotionality is measured as the three neuroticism measures utilized were significant mediators whereas the HEXACO emotionality scale was not. A facet-level analysis was conducted with the IPIP-NEO facets of volatility and withdrawal and with the HEXACO facets of sentimentality/dependence and withdrawal. In either case, withdrawal was a significant mediator in the materialism well-being relationship, whereas volatility or sentimentality/dependence was not. The results highlight the differences between neuroticism and HEXACO emotionality and add additional insight into the relationship between materialism and lower well-being. These findings suggest possible methods of decreasing materialistic tendencies and increasing subjective well-being.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".