Earthkeepers Project: Noklak Border Mission
Bibliographic record
Abstract
This article describes exploratory eldwork in Noklak District, Nagaland, conducted by the Earthkeepers team based at The Highland Institute, Kohima, in April 2023. The Earthkeepers Project is an environmental humanities initiative funded by the International Development Research Centre (IDRC), Canada, and the team comprises three Canada-IDRC Myanmar Research Fellows and one coordinator. Broadly, the Fellows are mandated to carry out climate-change-related research along the Indo-Myanmar border from the Indian side. Speci cally, the team is collecting indigenous ecological knowledge and farmers’ perceptions of climate change. In this report, we describe our Noklak study area and the Khiamniungan community residing there, give short notes on the villages visited, and brie y record our observations on the local people’s climate change perceptions and the challenges facing a community divided by an international border.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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; both teacher heads agree on what is shown here.
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".