Modeling consumer home composting intentions for sustainable municipal organic waste management in Iran
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<abstract> Home composting (HC) can be a cost-effective strategy for organic solid waste management. This option is also desirable since HC is increasingly automated, with HC machines composting faster than conventional composting in outdoor settings. Besides, HC may reduce organic solid waste management costs, especially for developing countries with scarcer resources. Taking Iran as a study case, the paper examines the influence of variables pertaining to the theory of planned behavior, the value-belief-norm framework, and the technology acceptance model. This study uses data collected from a territory-wide survey (n = 367) of Isfahan's residents to predict HC intentions. The results show that both attitude and subjective norms appear as the most impactful of all variables. These results further vary according to sex, with women being significantly more prone to HC than men. The findings may provide a reference to implement HC in Iran and other developing countries and possibly developed ones. </abstract>
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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