THE ROLE OF RESGUARDO LAND ACCESS AND LANGUAGES IN THE INCOME DISPARITY AFFECTING COLOMBIAN INDIGENOUS PEOPLE
Bibliographic record
Abstract
This paper addresses the question 'Do land access through resguardos (reserve lands) and ethno linguistic alienation/integration contribute to the relative income poverty of Colombian Indigenous peoples?' To answer this question this investigation regressed the (log of) income unmet basic needs (IUBN) gap between Indigenous and non-minority people on a set of explanatory variables that included: the mean resguardo land size per family (as an indicator of land access) and the percent of Indigenous populations (at the municipal level) that speak Spanish and those that speak their Native language (as indicators of ethnolinguistic alienation/integration). The research results suggest that, for the Andean region, ethnolinguistic integration (speaking a Native language) was in important factor in decreasing the IUBN gap but, for the Amazonian region, ethnolinguistic acculturation (speaking Spanish) increased the IUBN gap. More resguardo land per family, however, tended to be associated with a larger IUBN gap. Further investigated suggested that this was likely due to the fact that resguardos tend to be large where lands are marginal and/or remote, making them economically unproductive.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".