Bibliographic record
Abstract
This chapter analyses human orientations related to current environmental issues and proposes positive creative responses in dialogue, especially with Martin Buber, Nick Black Elk, Pope Francis, Lynn White Jr, and Edith Stein. It illustrates the problems in relation to Indigenous peoples and coloniality contexts, highlighting both distorted and reverential approaches to trees through consideration of a concrete historical case—the radical depletion and degradation of the white pine forest ecosystem of Ontario and other areas of eastern North America from the seventeenth to the nineteenth century. The chapter (i) compares this Canadian/USA context with current conditions in the Amazon rainforest of South America; (ii) analyses core traditional distorted human attitudes that contribute to such environmental destruction and sociocultural repression, in which trees are solely objectified, hypercommodified, and radically exploited; (iii) points to supportive and personally transforming attitudes towards trees—especially through Jewish-philosophical and Indigenous models—that highlight their intrinsic value and our potential relationship with them, in respectful, appreciative, nonintentional, and deeply spiritual ways; and (iv) relates the dialogue with contemporary socioeconomic concerns and interests.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".