Resilience, Resourcefulness and Creativity: Learning from the Diversification of Guatemalan Artisans during the Pandemic to Sustain Textile Traditions
Bibliographic record
Abstract
Coronavirus detrimentally impacted textile craft production and the income of indigenous artisans, including those working in the Lake Atitlán area. The article focuses on how five enterprises diversified their entrepreneurial practices and actioned strategies to support their communities during the crisis. Interviews with host textile companies based in Guatemala, the US and UK were conducted to inform case studies documenting the artisans’ experiences, the pandemic response and implications for the long-term effects on the sector. The research highlights the creative resilience of the artisans; how regional lockdowns restricting the transport of materials and provisions, led to a regional sharing economy. The crisis highlighted the advantages of home-working, belonging to co-operatives and the benefits of partnerships with NGOs for accessing essential resources, income and routes to market. Despite the loss of local income streams, engagement with and investment in digital platforms opened up new communication and sales channels, enabling artisans to maintain revenue.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".