Legal Pluralism, Transitional Justice, and Ethnic Justice Systems
Bibliographic record
Abstract
Colombian law recognizes that traditional Indigenous and Black authorities can exercise legal jurisdiction and apply their laws and traditions in their ancestral territories. Despite this legal recognition, the legal system does not operate in a way that genuinely guarantees legal pluralism. In practice, higher courts repeatedly overturn or dismiss decisions by indigenous legal authorities. As a result of the 2016 Peace Agreement between the Colombian Government and the former guerilla of the Revolutionary Armed Forces of Colombia – The People’s Army (“FARC-EP” in Spanish), a transitional justice tribunal was established: the Special Jurisdiction for Peace (“SJP” or “the Special Jurisdiction”). The Special Jurisdiction’s main task is to investigate and try the most serious crimes committed during the armed conflict, a conflict that has disproportionately impacted racialized communities. The SJP, unlike other tribunals in Colombia, has sought to adapt its work to meet the reality of legal pluralism by: 1) negotiating protocols for inter-jurisdictional interaction between the SJP and ethnic authorities, 2) consulting with Indigenous and Black communities on the adoption of some legal instruments, and 3) having a dialogue between equals with ethnic authorities when potential jurisdictional conflicts arise. This paper seeks to analyze this interaction and how it has allowed the Special Jurisdiction, as transitional justice mechanism, to work in close cooperation with Indigenous and Black communities in Colombia. As will be discussed throughout this paper, through the lens of the legal pluralism framework, such interaction has strengthened the legitimacy and recognition of Indigenous and Black communities’ legal authorities as parallel legal orders that can operate side-by-side with the State judicial system. This, in turn, has created an important precedent that can be emulated by other court jurisdictions in Colombia and elsewhere.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.040 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.008 |
| 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".