Clarifying the Challenges: A Response to Zhiwa Woodbury's Review and Response to <i>Radical Ecopsychology: Psychology in the Service of Life</i> (2nd Ed.) by Andy Fisher
Bibliographic record
Abstract
In this response to Zhiwa Woodbury's review of my book Radical Ecopsychology (2nd ed.), I clarify positions of mine that I believe Woodbury presents either inaccurately or inadequately. I do this by placing his comments and criticisms within the context of the issues I think they raise about the development of ecopsychology: the conflict between the inherent radicalism of ecopsychology and the historical conservatism of psychology; the need to develop critical distance from eco-destructive systems that need to be transformed or transcended; the challenge of preserving the truths that are essential to ecopsychology as we attempt to move from periphery to center; and the need to offer new images as part of the process of ecological social change. I comment throughout on the relevance of my argument that ecopsychology is inherently radical for making sense of the first-generation/second-generation ecopsychology crossroads.
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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 | 0.036 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.014 | 0.025 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.040 | 0.065 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".