“Landscape Ecology in the Mediterranean: inside and outside approaches”
Bibliographic record
Abstract
Relationships with all the other beings that inhabit the living environments of human societies have evolved over time and continue to do so. A book such as Philippe Descola’s (“Beyond Nature and Culture”), which aims to order these relationships by identifying the underlying schemes of practices, is of interest to all people dealing with the environment today. Starting from the ways “the other” is identified, his analysis leads him to develop four ontologies (animism, totemism, naturalism and analogism). These enable him to classify human societies according to the way they consider other non-human beings and to the relationships they entertain with them. This endeavour has not failed to generate criticism, mainly from anthropologists who do not recognize the features proposed by the author in the societies they have investigated. Therefore, we needed to follow his reasoning step by step in order to understand the arguments which are to be questioned or adhered to. We consider first the relevance of the division into four ontologies. We then criticize some aspects of the author’s approach and especially the way he avoids dealing with the dynamics that have affected human societies over time, especially in their relationships with animals and plants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".