A growing sense of well-being: a literature review on the complex framework well-being.
Bibliographic record
Abstract
This review examines the origin and structure of the complex well-being (WB) concept as it is currently applied in behavioral and social sciences. Current research on WB is often divided into two perspectives: subjective well-being (SWB) and psychological well-being (PWB), shaped by the philosophical concepts of hedonism and eudaimonism, respectively. How these different views relate to each other and to WB as a whole has not yet been clearly defined, leading to difficulties in interpretation. In this review, we aim to get more insight into the relation between SWB and PWB. We first present an overview of the philosophical history of SWB and PWB, followed by a systematic literature review. The goal of this review, based on 29 studies, was to investigate how much evidence there is for a conceptual overlap between SWB and PWB. A majority of the studies found appreciable shared variance between the constructs, suggesting that they might be more closely related than previously assumed. On the other hand, evidence from biological studies provides mixed results: a distinction between SWB and PWB based on unique biomarkers is reported, while recent molecular genetic studies show strong genomic overlap between SWB and PWB, but different gene-expression regulation. We end with a discussion on how these findings fit into a well-being framework, and describe some of the issues in the well-being field as we encountered them in our review followed by potential solutions to these problems.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".