Positive orientation: explorations on what is common to life satisfaction, self-esteem, and optimism
Bibliographic record
Abstract
Aim– Literature documents that the judgments people hold about themselves, their life, and their future are important ingredients of their psychological functioning and well-being, and are commonly related to each other.Methods– We used confirmatory factor analysis (CFA) under the classical test theory, regression analysis, and a cross national design.Results– This study provides new findings attesting to the hypothesis that evaluations about oneself, one's life, and one's future rest on a common mode of viewing experiences which we named “Positive Orientation”.Conclusions– Results from an Italian and a Canadian study are resented, attesting to a latent dimension that lies at the core of positive evaluations and that corroborates the utility of the new construct as a critical component of individuals’ well-functioning. Declaration of Interest:This study was partially supported by Grants from the MIUR, 2002 and 2005, and by a Grant from the University of Rome “La Sapienza”, 2002 to Gian Vittorio Caprara. Authors declare “no potential conflict of interest”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".