Institutions for Civic Technoscience: How Critical Making is Transforming Environmental Research
Bibliographic record
Abstract
This article explores the changing relationship between the academy and new public formations of scientific research, which we term “civic technoscience.” Civic technoscience leverages tactics seen in critical making communities to question and transform how and who can make credible and actionable knowledge. A comparison of two case studies is used. The first is a grassroots mapping process that allows communities to generate high-quality aerial imagery. The second is an academic-led project using environmental sensors to engage disparate audiences in scientific practice. These two projects were found to differ in their ability to form strategic spaces for community-based science, and suggest pathways to foster more robust relationships across the public–academic divide. By altering power dynamics in material, literary, and social technologies used for scientific research, we argue that civic technoscience enables citizens to question expert knowledge production through critical making tactics, and creates opportunities to generate credible public science.
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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 | 0.023 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.019 | 0.073 |
| Scholarly communication | 0.036 | 0.024 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".