‘Unaffected by Fortune, Good or Bad’: Context and Reception of Chandrasekhar's Mass–Radius Relationship for White Dwarfs, 1935–1965
Bibliographic record
Abstract
Summary The 1935 conflict on the nature of relativistic degeneracy that pitted Subrahmanyan Chandrasekhar against Arthur Stanley Eddington is part of astronomical lore. In recountings of the events surrounding the dispute, the complaint is frequently aired that Chandrasekhar, who faced the pre-eminent astrophysicist of his time, did not enjoy the support of the astronomical community, which opted to side instead with Eddington. We reconsider these statements in the light of the published record and argue that the reception of Chandrasekhar's ideas was, if anything, rather favourable and that any perceived lack of support may have been due in great part to the inability to distinguish, on an observational basis, between the predictions of the competing theories. We further argue that the observational situation improved little over the subsequent thirty years, but that this did not prevent Chandrasekhar's version of relativistic degeneracy, and associated theory of electron-degenerate stars, from gaining a central position within the realm of stellar structure and evolution. We briefly compare this status to that enjoyed by general relativity before 1960.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| 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".