Examining waste management in San Pablo del Lago, Ecuador: a behavioral framework
Bibliographic record
Abstract
Purpose The purpose of the paper is to propose and examine with evidence from Ecuador a behavioral framework that helps understand environmental practices in a small rural community. Design/methodology/approach This research is a multidisciplinary study that integrates ethnographic, feminist, and fourth generation approaches. Qualitative and quantitative methods were applied. Findings Findings indicate a number of relevant determinant factors (social norms, personal norms, intention to act), moderating factors (knowledge of the issues, awareness of the consequences, knowledge of the strategies and action skills, assumption of the responsibilities), and socio‐demographic factors (gender and social class) that influence solid waste (garbage) management behavior in a small rural community in the Ecuadorian Andes. Practical implications This study recommends general public training for the stakeholders of this community taking into account gender and social class differences. The importance of generating role models in groups such as business owners and teachers to lead in waste management behavior is also suggested. Originality/value This study develops a behavioral framework with supporting empirical evidence from Ecuador that aids the understanding of environmental management practices of women and men from a small cohesive community
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".