Exploring resilience in public services within marginalised communities during COVID-19: The case of coal mining regions in Colombia
Bibliographic record
Abstract
This paper examines the impact of COVID-19 on marginalised communities and its effects on the provision of public services. Focusing on two coal mining regions in Colombia during the pandemic crisis, and examining Indigenous and Afro-Colombian communities, we analyze the provision of public services at a local level, identifying both shortcomings and resilience. Findings show that the lack of resilient public services amplified the effects of COVID-19 and its containment measures, exacerbating existing structural inequalities within local marginalised communities. It also reinforced the control exercised by coal mining companies within local economies. However, the substantial lack of public service provision also provided space for the development and strengthening of several resilience strategies among local communities, such as solidarity networks and schemes and the revitalization of local environmental knowledge. The study identifies multiple shortcomings in how the national and local administrations handled the COVID-19 outbreak and highlights the potential of enhancing resilience in public services to support marginalised communities in times of crisis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".