Speculative science ("fairy tale science") in physics, cosmology, and economics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The paper juxtaposes two recent books dealing with reality issues in a broad sense. The first of these, by Baggott (2013,) examines and criticizes the historically increasing trend to base scientific conclusions on mathematical hypotheses and logical consistency rather than on empirical evidence -- Bagott calls this trend “fairy tale science”. The second book, Tegmark (2014),i defends the opposite view – it considers Mathematics as identical to Reality and promotes increasing reliance of modern physics and cosmology on mathematical assumptions and logical consistencies rather than empirical evidence -- defending such controversial conclusions that we live in one of infinitely many parallel universes with numerous alter egos of each of us. But this is not a book review of Baggott (2013) and Tegmark (2014); its aim is to draw attention to the fact that social scientists are not the only scholars blamed for paying too much attention to model building and too little to empirical confirmation. This, ought to be of enormous interest to financial scholars; it may even be a consolation to some of them for emphasizing mathematical consistency rather than empirical confirmation. But our examples (from “speculative science” in finance) illustrate that such a trend caused staggering losses during the financial crisis of 1997-1998 (of Japan and Russia) and serious threats to the entire World Economic System during the crisis of 2007-2008
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it