Utilising Mythopoetic Paradigms for Subverting Prescriptive Linguistic Colonial Supremacies
Bibliographic record
Abstract
Post-colonial scholars often confront the dual nature of colonial languages. While these languages provide pivotal communication avenues, especially for diverse marginalized groups like certain Indigenous communities, they simultaneously embody colonial biases, making them challenging mediums for emancipatory discourse. This paper proposes mythopoeticism to leverage the extensive reach of such languages, circumventing their constructive norms. We spotlight this through the prism of the Chiapas Mesoamerican communities' mythopoetics during the 1994 National Army of Zapatista Liberation (EZLN) uprising. This investigation aims to enrich contemporary post-colonial thought, presenting Mesoamerican perspectives on mythopoetics as a dynamic instrument for post-colonial dialogue. The discussion first examines the formative influence of colonial languages on meaning and power dynamics. It then transitions to a detailed textual analysis of the Zapatista mythopoetic narratives. Lastly, it considers the assimilation of Mesoamerican insights into current post-colonial frameworks, endorsing mythopoetics as a rejuvenated mechanism for post-colonial endeavors.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.062 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".