What Is the Role of Public History and Environmental Oral History in Supporting Conservation through Agroecology?
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
Indigenous peoples and local communities are key actors in the preservation of important biodiversity resources around the world. However, the ever-encroaching agricultural frontier and expansion of conventional agricultural practices threaten these communities, their autonomy over the land, and the traditional knowledge and practices associated with biodiverse ecosystems. Agroecology emerges as an important solution to support the continuation of agrobiodiversity, food security, and environmental conservation, but top-down solutions often do not resonate with the lived realities of traditional, Indigenous, and small-scale farming communities. This paper examines a collaborative research and narrative network developed over the past several years around traditional erva-mate agroforestry production in Southern Paraná, Brazil. It offers an example of how oral environmental history and public history can support conservation practices through agroecology. The key outcomes of this interdisciplinary, multi-dimensional research and engagement were the development of a candidacy for the system to be recognized as a Globally Important Agricultural Heritage System (GIAHS) from the Food and Agricultural Organization of the United Nations (FAO) and the implementation of a Dynamic Conservation Action Plan to address the threats and challenges farmers and communities are facing. The discussion explores two concepts that were integral to these processes, the creation of narrative networks and a focus on plurivocity. Both approaches ensured that the actions, knowledge, and narratives developed through the GIAHS candidacy were not imposed but agreed upon and generative through narrative and dialogue, remaining true to the realities and lived experiences of community members.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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