Bibliographic record
Abstract
Nobuko Iijima, a pioneer of environmental sociology both in Japan and internationally, applied her notion of the social structure of victims to the multidimensional and multi‐layered nature of the damage caused by pollution (Iijima 1976, 1979, 1984). The physical damage done to victims is relatively easy to discern, but this is only one aspect of pollution damage. Equally costly is the mental and social damage that occurs in the wake of the physical impact. Iijima attempted to describe comprehensively the complex structure of the suffering of victims, from physical suffering to worsening relationships between family members and neighbors who may be indifferent to the pollution problem or wish to keep it hidden. This approach reveals the flow‐on effect of the physical damage. In fact, Iijima demonstrated how such suffering affects every aspect of a family's daily life, including loss of income and an increase in medical expenses, and often leads to family breakdown or the destruction of a family's living conditions. Through her research on Minamata disease, mercury poisoning of Canadian Indians, and drug‐induced Subacute‐Myelo‐Optico‐Neuropathy (SMON) disease, Iijima discovered that the structure of victims was very similar whether the damage was caused by a labor accident, a drug‐induced disease, or an environmental hazard. The source of the pollution that caused Minamata disease was a factory already known as the site of numerous labor accidents. A systematic and institutional lack of care or consideration by industry and government for the safety of people's environment and the safety of working conditions nurtured the endemic problems that led to the Minamata outbreak.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".