Responsibility as humans: meaning of traditional small grains cultivation in Japan
Bibliographic record
Abstract
Small grains are a group of ancient grains that have been cultivated in different parts of the world for thousands of years, have high nutritional value, are resistant to drought, play a key role in agricultural resilience, and are adaptive to climate change. Of emerging concern globally, however, is that several varieties of small grains and related agricultural knowledge and practices are disappearing owing to the promotion and efficiency of industrial farming methods, agricultural intensification, and marked shifts in generational commitment to small grains cultivation and changing relationships with the land. This case study presents the findings of an in-depth ethnography of a farmer in Shiiba Village, Japan, who grows local varieties of small grains using traditional shifting cultivation methods. Explored in this study is the meaning of small grains cultivation and benefits and significance of this practice for a farmer and the implications for society and the environment. Four themes related to meaning emerged from this case study: (a) small grains cultivation is a source of life across generations; (b) harmony: restoring the forest and co-existing with wild animals; (c) collaboration and revitalization of the local community; (d) a way of life. As a result of the meaning of the practice and his commitment to ensure the survival of small grains cultivation, a potential pathway is introduced involving collective responsibility and the contribution to the health of humans and the ecosystems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.025 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".