Bibliographic record
Abstract
In For Emplacement, Mario Blaser proposes a new lens for contending with the momentous challenges facing the world, from anthropogenic climate change to rampant socioeconomic inequalities to the rise of neofascism. Blaser shows that the prevalent solutions to these problems—which often depend on intensifying globalization, technological development, and extractivism—only deepen these crises. Effectively addressing these issues, he suggests, might require grounding our ways of being in the specificities of place. Drawing on decades of ethnographic experience in South America and the Canadian subarctic, and engaging with material semiotics, Blaser recasts the fundamental political question of how to live together well as a cosmopolitical one: how to become emplaced with others, in divergence. Ultimately, he presents a political ontology where visions of the good life oriented to the specificities of place guide us through the promises and challenges that a journey toward emplacement holds.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.011 | 0.021 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.090 | 0.046 |
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".