“Matters” of Importance: Contaminated Materiality in the Aftermath of the Fukushima Disaster
Bibliographic record
Abstract
Contamination has been viewed as a form of invasion—an intrusion perpetrated by a group, a pernicious substance, or an unwanted agent. It is ‘the Other’ that has fascinated anthropologists for so long. We often assume that our current theory of knowledge about contamination is justified—although this current understanding fails to take into account the agency of contaminants themselves. Ideas about contamination throughout history have helped to fashion a particular dichotomy—a dualism where infection contrasts against wellbeing, where purity confronts impurity, and where ‘pristine’ nature opposes toxic landscapes. However, this binary understanding is often a double bind that does not reflect all of the nuances involved in contemporary problems, such as ecological disasters. For this reason, anthropologists have a lot to gain by focusing on matter – that is – to envision the agency of given materialities as a complementary topic to the analytical processes surrounding contamination. For instance, what actually happens if we consider that contamination “refuses” to recognize our political, social, and cultural boundaries? This article attempts to reconceive the notion of contamination by targeting the materiality of contaminants, particularly nuclear radioactivity in relation to the Fukushima nuclear disaster in Japan, in order to theorize a hybridized (i.e., non-binary) understanding of contamination—an understanding that better reflects the ways in which societies, governments, and individuals think about and interact with matter.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.034 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".