Bibliographic record
Abstract
ContRAdiCtionS oF HopE And dESpAiRThe dystopia thesis is an analysis of humanity's most serious problems of the present and a prediction of them being exacerbated and added to in the near future.I have presented this thesis in some detail in my 2010 book Dystopia: What is to be done?I also made a documentary film of the same name that is available for free viewing (http://www.DystopiaFilm.com).What I intend to do here, is to give a summarised flavour of the overall argument presented in the book and film, but also add some reflections upon the utopian dreams of both right and left, and more importantly consider the Left's continued failure to construct a left vision that captures ordinary people's imagination and enthusiasm.The dystopia thesis propounds an argument that the structural features of the world political economy are such as to make the problems we collectively face impossible to solve.The dystopia thesis is grounded in present day fact and highly probabilistic trajectories and outcomes as regards the future.The logic and empirical content of the dystopia thesis concludes a near certain hopelessness with respect to avoiding a future of unimaginable horror and suffering.Causally inter-connected, mutually enhancing catastrophes, are around the corner . . .and there is nothing we can do to prevent them Yet at the same time, the dystopia thesis was founded on the contradiction of pessimistic assessment and sincere hope.If one believed absolutely in the hopelessness of any effort to avert catastrophe what would be the point in articulating the argument?
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.055 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".