Land‐based literacies in local naturecultures: Walking, reading, and storying the forests in rural Colombia
Bibliographic record
Abstract
Abstract Land‐based literacies scholars have worked to expand understandings of literacies to include often marginalized cultures who understand literacy as resulting from human and more‐than‐human relations. In this article, we contribute to this broadening of literacies with an analysis of how nature influences the meaning‐making practices of rural, subaltern communities in the Global South. Our inspiration stems from indigenous scholars who have advanced indigenous and relational epistemologies, seeking to bridge the nature/culture divide that remains prevalent in Western thinking. The central question that guides this article is: How are Land‐based literacies produced through the felt and sensed relationships with nature, history and culture in the Callemar community? Drawing on micro‐analysis of participant‐generated video data from two walks with Colombian youth and adults from the Callemar community, we illustrate ways naturecultures, specifically the assemblages of Land, collective memory and cultural practices, produce Land‐based literacies. We describe Land‐ walking, including forest‐ and creek‐crossing practices, as literacies that require reading and meaning‐making with the Land, and that which allow individuals to relate to other beings and thrive in the changing landscape of their rural community. Our description and discussion of Land‐based literacies in this rural community poses important implications for informing pluriversal literacies pedagogies that draw on local knowledges and contexts to make literacy learning more relevant and equitable. Furthermore, we describe the relevance of Land‐based literacies for sustainable stewardship of the Land during times of drastic environmental change.
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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 | 0.001 | 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 | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".