Maturity of Jurisdictional Abandoned Mine Programs in Australia Based on Web-accessible Information
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Bibliographic record
Abstract
In Australia, responsibility for abandoned mines can be unclear. With a few exceptions, state and territory governments have become responsible for abandoned mines on Crown land and private landholders are responsible for abandoned mines on freehold land. Abandoned mines pose risks and opportunities across the full suite of sustainability themes (environmental, human health and safety, socio-economic and community development) after mining ceases. \n \nAcross Australia, there are more than 50 000 abandoned mines recorded, ranging in size from individual shafts to large polluting open cut mines. Addressing the safety and environmental impacts of these sites, as well as the socio-economic development opportunities of significant rehabilitation projects, requires the implementation of effective policies and programs. Qualitatively defined graded scales or ‘rubrics’ have been used for many years in student assessment and increasingly in the performance assessment of other sectors (Davidson, 2005). While risk-based maturity models have been used for safety prioritisation (Westrum, 1993; Hudson, 2007; DRET, 2008; Hancock, 2010) and evaluation of organisational development (Esteves et al, 2010), this paper is the first to adapt maturity models for the evaluation of abandoned mine rehabilitation programs in Australia. \n \nIn this paper, we used indicators based on the national policy for abandoned mines to assess the maturity of abandoned mine programs. Fourteen elements of maturity were identified (Unger et al, 2012) under the five chapters of the national policy for abandoned mines (MCMPR and MCA, 2010). Jurisdictions were then evaluated and ranked on their maturity on the basis of information that was web-accessible. Information transparency of abandoned mines policies and programs is in itself one element of the maturity chart. Each jurisdiction in Australia was compared with one another and with a Canadian jurisdiction; the British Columbia (BC) Crown Contaminated Sites Program (CCSP), which represents leading practice (Unger, 2009; Unger et al, 2012). \n \nOur research found that in some jurisdictions in Australia there is little or no information on abandoned mine programs or individual abandoned mine sites on government websites, while other jurisdictions provided very detailed program information on planning, funding and implementation. Each jurisdiction in Australia, for which web-based information was available, had some elements where they were more mature than other Australian jurisdictions. For some elements, maturity ranked equivalent to the BC CCSP, but most Australian jurisdictions were less mature. There was only one element where a single Australian jurisdiction ranked higher than the BC program in maturity. Legacy mine policies, programs, priorities and funding information via departmental websites are easier to find in some jurisdictions, indicating progression toward greater transparency and more mature programs. A systematic approach to monitoring and evaluating abandoned mines programs is essential for accountability as it can demonstrate liability reduction over time and continual improvement. The maturity model approach can provide both a measure of progress over time as well as a tool to support the implementation of the national policy for abandoned mines (MCMPR and MCA, 2010).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 it