Ultra‐Orthodox recycling narratives: implications for planning and policy
Bibliographic record
Abstract
Purpose Recycling facilities are not available in most Ultra‐Orthodox (Haredi) Jewish neighborhoods in Israel. Servicing Ultra‐Orthodox communities would offer significant relief for rapidly bloating landfills. Haredi communities have highly religious lifestyles, very large families and tend to cluster together in communities, posing significant challenges in urban planning and policy. With careful planning and education these communities have the potential to be high‐yield recyclers, as the act of recycling plastic, paper and glass is not religiously prohibited. The purpose of this paper is to determine the feasibility of installing recycling facilities in two Ultra‐Orthodox neighborhoods in Jerusalem. Design/methodology/approach Data were collected by administering a short questionnaire to neighborhood residents and asking them questions about recycling behavior as well as demographic information. Findings Ultra‐Orthodox communities have a unique recycling narrative which determines the materials they are most likely to recycle. Rabbinical leaders and monetary incentives are instrumental in garnering support for recycling programs. Research limitations/implications The findings shed light on demographic variables which influence recycling behavior such as age, gender, household size and religiosity/ethnicity. Practical implications The rich data have significant planning and policy implications. As this study relies on statistically significant data, it is highly likely that the conclusions drawn are applicable to other Haredi neighborhoods and beyond. Originality/value As a whole, Ultra‐Orthodox attitudes and behaviors exposed in this study reveal, for the first time, a religious ethnography of recycling or a recycling narrative.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".