Bibliographic record
Abstract
I was thrilled to review a book uncovering green colonialism and exploring how environmental discourses and policies can be used as tools of dispossession. While its synopsis clarifies the focus on the African continent, the book concentrates on the violence in the context of the Simien Mountains National Park in Ethiopia. This narrow scope contributes to some of the book's generalizations and contradictions, which undermine the credibility of what is otherwise an informative and innovative contribution. For instance, Guillaume Blanc closes his acknowledgements stating that ‘this book should be signed by all the inhabitants of the Simien Mountains in Ethiopia’ (p. xiv). Even if this nod is well intentioned, it insinuates that all locals approved of or contributed to his project. This is a grandiose claim to be made by anyone, let alone a non-Ethiopian scholar who scarcely cites inhabitants from the region. In a 2022 interview about this book, Blanc challenged the notion that Indigenous communities are more inherently environmentally friendly than Europeans, out of his concern for ‘reverse racism’ (pp. xi and 136). However, racism is entrenched worldwide in white supremacy. The latter privileges white people while subjugating others, and thus cannot be inverted. Hence, it is rather oppressive for Blanc to make this argument, especially given how colonial powers have conceived of Indigenous peoples as ecological savages, dehumanizing and justifying abuse against them (see Ghada Sasa's, ‘Oppressive pines: uprooting Israeli green colonialism and implanting Palestinian A'wna’, Politics, October 2022).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".