Union and Communist Party Influences on the Environment in China
Bibliographic record
Abstract
We examine the ways in which two major and related governmental institutions of China, the Communist Party of China (CPC) and government controlled All-China Federation of Trade Unions (ACFTU), exert different effects on the attitudes and behaviour of people toward the environment. Our motivation is to see which institution is more effective in making individuals ‘aware’ of environmental issues, expressing a ‘willingness to pay’ to alleviate the problems, and ultimately to ‘act’ on the issue by altering their behaviour. Based on theories of planned behaviour and social learning, we hypothesize that membership in the CPC as well as in the ACFTU fosters an ‘awareness’ of environmental problems and a ‘willingness to make a sacrifice’ to protect the environment, but that members of the ACFTU are more likely than members of the CPC to act on the issue by altering their behaviour. We test our hypothesis based on a nationally representative sample (n = 3112) from the2010 Chinese General Social Survey(CGSS). Our results indicate that both the Party and the union have positive effects on ‘awareness’ and ‘willingness to pay’, but the union effect is generally stronger and only it (and not the Party) affects individual behaviour toward protecting the environment. Unions in China are generally regarded as having little or no independent power to organize workers and engage in free collective bargaining. Their role is to foster harmony between workers and employers and to co-opt grassroots actions, wildcat strikes and the growth of independent unions, all in the interest of fostering stability and growth. While this is undoubtedly the case, our results are consistent with an emerging view of a more variegated picture of Chinese trade unions that highlights some more positive elements, in our case, fostering ‘actions’ to improve the environment in China.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".