Another Attempt to Move Beyond the Cross-Sectional U Shape of Happiness: A Reply
Bibliographic record
Abstract
In this reply to Blanchflower and Graham (2021), we address key points in their response to our article, which challenged the robustness of the U shape in different contexts and aimed to move scholarship on life-course happiness beyond a focus on a single cross-sectional curve. We attend to apparent misconceptions in their portrayal of our arguments, identify points of agreement, and emphasize the value of exploring diversity rather than searching for homogeneity in patterns of change in well-being across life. Future longitudinal research to uncover the complex processes that characterize and underlie human happiness will lead to greater understanding that can benefit individuals and societies.
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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 | 0.027 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.049 | 0.079 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".