Counterhegemonic Forms of Justice: The Potential of Permanent Peoples Tribunal in the Context of Resource - based Conflicts and Human Rights Violations in Guatemala
Bibliographic record
Abstract
This thesis is about the confrontation between two forms of justice. One institutionalized as law, and the other, depending on situational embodied forms of doing justice. Further, it is about the confrontation between sources of law. One source relates to sovereign nation states as top down mechanism, and the other, to indigenous peoples as bottom-up process. The analysis applies a bottom-up approach, as suggested by decolonial critical thought, that questions elemental assumptions about dominant neoliberal institutional frameworks. This thesis cannot solve these tensions. It tries to investigate their dynamics on the basis of a specific case, which is, the ethical tribunal, established by Maya Mam indigenous peoples in 2012, that accuses the Canadian mining company Goldcorp for committing human rights violations through its extractive activities in the area of San Marcus Ixtahuacán, Guatemala. Instead of coming up with a solution, the thesis wants to question dominant legal frameworks that permit human rights violations and reveal the capacity of informal legal compositions to install grounds of justice. It was identified that the ethical tribunal contributed to unfold the seemingly uncontested nature of neoliberal extractive activities through its potential to challenge impunity and establish access to cognitive, and epistemic forms of justice.
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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 | 0.002 | 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 | 0.017 | 0.032 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| 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".