Temporality and justice in mining impacted regions
Bibliographic record
Abstract
Abstract The accelerating impacts of climate change call for urgent action to decarbonize our socio-technical systems based on coal and oil. Frequently, these shifts involve decisions made in distal capital cities, or distant countries, that have significant impacts on resource-based communities. Among those impacts, we focus on temporal justice: the disjuncture between the timeframes of urgent decisions about transition options to meet policy objectives and the timeframes experienced by residents of regions affected by those decisions. This article reveals how these impacts fit within trajectories of change in energy-related resource-extracting regions through six case examples in Australasia (Hunter Valley, Latrobe Valley, West Coast region of New Zealand), Canada (Alberta), and Africa (Ghana, Zimbabwe). Each setting is at a different point in the mine lifecycle (from exploration and planning of new mines, through to closure, rehabilitation and relinquishment). Included are places where residents mourn the past glory days of coal to regions where closure is imminent, to regions wary of the rush to start new mines for energy transition minerals to support increases in electrification. Collectively, the case studies illustrate the varied complexity of energy transitions and how multiple forms of justice (environmental, procedural, recognition, restorative, distributive and intergenerational) shape the key issues and required responses to transition challenges. The cases highlight the notion that a capacity for local communities to respond to these changes is impacted by embedded senses of identity, agency in the transition process, and a legacy of past activity and injustices. Because each of these factors takes time to work through, there is a disconnect between the urgency of transition due to growing global impacts and the time required for host communities to become effective participants in their own local transitions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".