Life is pretty meaningful and/or purposeful?: On conflations, contexts, and consequences.
Bibliographic record
Abstract
Comments on the original article "Life is pretty meaningful," by S. J. Heintzelman and L. A. King (see record 2014-03265-001). Heintzelman and King condense descriptive data from numerous studies to conclude that individuals tend to see life as meaningful, because average scores on the meaning and purpose in life assessments fall above the midpoint. However, in so doing, they make two contentious assumptions. The first is the expectation that scale midpoints actually reflect an average score on that construct. However, one should not interpret this metric to suggest that people generally live meaningful lives without great caution and consideration of the second assumption: the conflation of purpose and meaning in life. In response, the current authors address this second assumption and the need to develop better questions and measures for both meaning and purpose.
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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 | 0.008 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.052 | 0.044 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".