Bibliographic record
Abstract
This paper engages my struggles to craft geo-graphs or earth writings that also further broaden political goals of decolonizing the discipline of geography. To this end, I address a body of literature roughly termed ‘posthumanism’ because it offers powerful tools to identify and critique dualist constructions of nature and culture that work to uphold Eurocentric knowledge and the colonial present. However, I am discomforted by the ways in which geographical engagements with posthumanism tend to reproduce colonial ways of knowing and being by enacting universalizing claims and, consequently, further subordinating other ontologies. Building from this discomfort, I elaborate a critique of geographical-posthumanist engagements. Taking direction from Indigenous and decolonial theorizing, the paper identifies two Eurocentric performances common in posthumanist geographies and analyzes their implications. I then conclude with some thoughts about steps to decolonize geo-graphs. To this end, I take up learnings offered by the Zapatistas. My goal is to foster geographical engagements open to conversing with and walking alongside other epistemic worlds.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.060 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".