Does Money Talk? Waste Charging in the Republic of Ireland: Government, Governance and Performance
Bibliographic record
Abstract
The question of how best to govern waste is a challenging issue across the globe. As a result, new policy instruments, such as voluntary agreements, eco-labelling and market based instruments, frequently identified as being emblematic of a shift from government to governance are being developed and implemented in an attempt to improve waste management. In particular, the introduction of pay-by-use (PBU) mechanisms, where charges are based on the weight or volume of waste presented for collection, have been cited as a key means to promote the polluter pays principle (PPP) in the waste field. However, most analyses of waste charges have attempted to quantify PBU impacts in terms of tonnes of waste diverted from landfill, recycled or dumped illegally, and less consideration has been given to their development and implementation from a governing perspective. In response, this paper reports on a nationwide survey of PBU in Ireland that revealed a general increase in recycling and diversion from landfill since it was introduced in 2005. The paper concludes that although such metrics seem to support the introduction of PBU they must be read within a dynamic policy context characterized by limited information, increasingly privatized waste services and neoliberal statecraft.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".