Bibliographic record
Abstract
Richard Powers is one of American famous contemporary writers, a rising star of American postmodernist fiction, and one of leading representatives of the Generation Xers as well. He explores the impacts of some factors such as ecological environment, social culture, and family ethics on our modern society by use of his abundant knowledge about gene engineer, neurology, family ethics, etc. He explores the relationships between human and nature, human and society, human and human. Generosity, fusing science with literature perfectly, is one of prominent information fictions by Richard Powers, which narrate a fascinating thoughtful story about the secret of happiness. From the perspective of ecological philosophy, this article explores human being ecology embodied in this fiction, which thinks that the earth is an ecosphere, also a largest ecosystem in which human being, just a part of it, is a small ecosystem and runs according to natural law. Ecological human being had his own ecology including physical property, social property and understanding and attitudes towards nature. Excessive human activity, especially the abuse of science and technology will result in destructive impact on human being ecology，bring about serious effect on normal running and harmonious evolvement of ecosystem containing human being and nature, and it must be faced squarely and solved urgently.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.037 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".