Rethinking the Sustainable Livelihoods Framework: An Indigenous Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sustainable Livelihoods Framework (SLF), a widely used analytical tool originating from development studies, aims to identify livelihoods dynamics and suggest solutions for marginalized populations. In this article we argue that a fixed asset model defined within the sustainable livelihoods framework limits adequate understanding of Indigenous culture and livelihoods and therefore fails to acknowledge the historical power imbalances. By making a critical analysis of the term "capital" used in the sustainable livelihoods framework, we argue that for an ethical understanding of development politics, the sustainable livelihoods framework should be supple and accord with a culturally appropriate analysis, definition and terms. This paper presented its argument based on O-Pipon-Na-Piwin Cree Nation's perspective on sustainable livelihoods and relationships.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it