Bibliographic record
Abstract
Abstract Mine closure is a global challenge. To date, there has been no scientometric analysis of the mine closure literature. This paper uses a scientometric analysis to assess the literature on mine closure. We assessed 2078 papers published since 2002. There was a rapid increase in the research output, with 76% of the papers published in the last 10 years. We identify the journals and co-citation index of journals associated with mine closure research. Geography journals are prominent with 20% of papers, but there is also evidence of journals linked to mining and interdisciplinary journals. Four clusters of universities are working on mine closure (the University of Western Australia, the University of Queensland, the University of the Free State and the University of Alberta) and the co-citation index groups journals into three clusters (environmental and ecological concerns, environmental health, multidisciplinary issues). The co-citation index groups the themes into 20 clusters, which we have regrouped into five themes (health, environment, geography, society, and regulation/politics). We draw seven conclusions. Although original social science research focused on the impact of mining, (1) there is clear evidence of work focusing on mine closure and (2) this work is rapidly increasing. The geography remains important (3) but has negative effects. Despite the geographical focus, ideas and concepts are substantially integrated across the available work (4). Focusing on geographical journals might prevent work from being published in multidisciplinary journals (5). Papers linking theory and mine closure are limited (6) and the available work needs careful thought on planning closures in cities and communities (7).
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 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 | 0.003 | 0.005 |
| 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 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".