How Did Work Attitudes Change in Reform-Era China? Age, Period, and Cohort Effects on Work Centrality
Bibliographic record
Abstract
Using a four-wave cross-sectional repeated dataset spanning 17 years (World Value Survey, 1990, 1995, 2000, 2007), this research examines changes in work centrality in China during the period of economic reform. The article utilizes a recently developed methodology, hierarchical age-period-cohort (HAPC) models, to disentangle the effects of age, period, and cohort. Results show that age has a curvilinear effect: work centrality increases up to middle age, then levels off. For period effects, there is a downward trend in work centrality in China between the 1990s and 2000s that is explained by economic growth. Though overall cohort effects are marginally significant, the study reveals that work centrality tends to be high among the “revolutionary socialism generation” but lower for the “post-800 generation.”
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".