Bibliographic record
Abstract
In Western Australia there have previously been very limited attempts to deal with the issue of household hazardous waste (HHW). This report presents the findings of a worldwide literature review to determine “best practice” in the collection of household hazardous waste. The Waste Division of the Department of Environment Western Australia determined the need for this review, to assist in developing their strategies to deal with the problematic household hazardous waste stream. \n \nThis research initially examined the legislative framework for the management of HHW within Australia, and overseas in Europe, United Kingdom (UK), New Zealand, Canada, United States, Africa, Asia, Hong Kong, Singapore, China and Japan. The research then focused on identifying and analysing the existing HHW collection systems within Australia and overseas, the collection methods that were used and the costs incurred. The research identified that countries where separate collections of HHW are organised, usually rely on a combination of methods to collect the HHW. \n \nExamination of the literature identified the costs of collecting HHW varied considerably between different countries and the various identified programs. During the research, it also became evident that a number of interesting initiatives for specific items of HHW were being undertaken, such as the Community RoPaint Program in the UK. \n \nEducation and promotion programs for the collection of HHW were also reviewed during the research, and it was apparent that the success of any HHW collection program is largely dependent on educating the public using all forms of media.
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.
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 | 0.076 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".