Development and preliminary testing of sustainable development indicators for biosolids management at regional/local level in Ireland
Bibliographic record
Abstract
Management of biosolids (treated sewage sludge) is becoming a significant issue for Local Authorities throughout Ireland, especially with the progressive implementation of the EU Urban Wastewater Treatment Directive 91/271/EEC of 1991. The future of biosolids management will depend on what direction Local Authorities take in the immediate future. This direction will be determined by quantity and quality of treated sewage sludge, types of sludge treatment available/selected and recycling/disposal outlets that will be acceptable to most stakeholders and most importantly, pose no danger to human health. The aim of this thesis is to develop and conduct a preliminary test of sustainable development indicators (SDIs) for managing biosolids at the regional/local level. Accordingly, a set of 22 SDIs (comprising five headline, seven core and ten complementary indicators) has been developed using a stakeholder-based approach. These indicators are arranged according to the Driving force-Pressure-State-lmpact-Response framework and address all domains of biosolids management namely, production, quality, cost, legislation/regulation, training/research and recycling/disposal. A preliminary test of the indicators was carried out in County Sligo to verify their suitability and usefulness. A key finding of the study is that the SDIs are relatively effective and can make significant contributions to the sustainable management of biosolids. The stakeholder participatory approach adopted in the study meant that the indicator development process involved participants from varied background, knowledge, experience and perspective. Such a ‘mix’ is necessary in order to capture the multi-faceted criteria of sustainable biosolids management. The methodology and analysis of the survey results were designed to ensure an unbiased, critical, and fair input by the participating stakeholders. The thesis concludes by synthesising the findings and making a number of recommendations and suggestions for further research. These propositions, if implemented, could lead to the refinement of the SDIs and generation of new ones.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".