The Paris Agreement: Climate Change, Solidarity, and Human Rights
Bibliographic record
Abstract
This book attempts to address the pressing question of how we might meaningfully address the myriad challenges posed by global climate change (GCC hereafter). Blau’s central thesis is that because climate is “collectively and globally shared,” the only way to solve the problem is “through acting in solidarity” (7). In contrast to the cutthroat individualism characteristic of American values, Blau emphasizes the importance of recognizing the environment as part of a “collective commons.” Focusing on the Paris Agreement as the most ambitious international effort to address GCC to date, this short book offers a succinct, readable overview of GCC and the framework of international human and environmental rights. The book is organized into ten short chapters (10–12 pp. each), though a quarter of this material (approximately 25 pp.) consists of “information boxes”—typically presented in bulleted lists (e.g., impacts and indicators of GCC).1 As such, The Paris Agreement may be more appealing to an advanced undergraduate readership, perhaps as a supplementary text for environmental sociology, political sociology, and/or social movements courses.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".