The emergence of a community mapping network: coastal eelgrass mapping in British Columbia
Bibliographic record
Abstract
The purpose of this paper is to document and theorize the emergence of a network of stewards concerned about the conservation of a marine habitat called eelgrass along the coastline of British Columbia, Canada. Today, by engaging as professional biologists, government employees, and volunteers using various mapping, outreach, and communication tools, these stewards generate knowledge on the geographic location and health of eelgrass habitat, how to educate the public, how to coordinate volunteers, and how to approach local governments--with the ultimate goal of convincing others that eelgrass is worth protecting. Our two-year ethnographic study began in the second year of a project that was designed to train twenty community coordinators how to map and monitor eelgrass habitat. The coordinators were faced with complex social, cultural, political, historical, and material landscapes--which made us wonder about how it was possible for the network to hold together while extending its reach. We provide evidence to support the claim that the network became more stable and was extended by particular performances. These performances emerged from recognition and resolution of resistances, in which the network was both resource for and object of its activity. In the process, (a) knowledge produced is made to move and do something, (b) coordinators and scientists involved acted as knowledge brokers between various communities, and (c) communication between coordinators was enabled and maintained.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".