Predicting residents’ adoption of living environment improvement practices toward sustainable development: the role of internet use
Why this work is in the frame
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Bibliographic record
Abstract
Improving the living environment through household efforts remains a challenge for many developing countries. Little attention has been given to the role of Internet use in previous studies. Based on the Attitude Behavior Context (A-B-C) theory, this paper builds a theoretical framework where Internet use affects residents’ adoption of living environment improvement practices (LEIPs). Using large-scale household survey data from China, this paper adopts the recursive bivariate probit model to overcome the endogeneity biases and investigate the treatment effects of Internet use on residents’ adoption of integrated flushing toilets (IFT) and centralized disposal of domestic waste (CDDW). The results indicate that Internet use increases the likelihood of adopting IFT and CDDW by 24.5% and 19.0% respectively for Internet users. Besides, the counterfactual results show that the possibility of adopting IFT and CDDW will increase by 28.8% and 26.4% respectively if they use the Internet. Moreover, residents who are female, the CPC members, having more years of education and higher household income are more likely to adopt LEIPs. Additionally, the results show evidence of regional heterogeneity. Overall, the impact of Internet use on LEIPs adoption is larger for residents in less-developed and urban areas. The findings suggest that policies embedded with expanding Internet access shall help to promote the sustainable improvement of residents’ living environment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it