Cultural Codes as Catalysts for Collective Conscientisation in Environmental Adult Education: Mr. Floatie, Tree Squatting and Save-Our-Surfers.
Bibliographic record
Abstract
This study examines how cultural codes in environmental adult education can be used to 'frame' collective identity, develop counterhegemonic ideologies, and catalyse 'educative-activism' within social movements. Three diverse examples are discussed, spanning environmental movements in urban Victoria, British Columbia, Canada, the redwoods of northern California, and the coral reefs and beaches of Hawai'i, respectively. The first, Mr. Floatie and his fight for sewage treatment, illustrates how art, humour and drama can be employed to mobilise the public, media and government to action. The second, Julia Butterfly Hill and her 738-day squat in a redwood tree, shows how cultural codes embodied in both tree and woman catalysed social action for forest preservation. The third, the grassroots organisation Save Our Surf, demonstrates the effectiveness of education and activism through immediate, multiple and short-term symbolic appeals for help, leading to long-term success in Hawaiian coastal conservation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| 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".