The Plague of Athens Shedding Light on Modern Struggles with COVID-19
Bibliographic record
Abstract
In 2020, we are facing unprecedented times, and as some form of lockdown continues with no signs of ending feelings of hopelessness are completely natural and understandable. Unprecedented times does not mean that these current issues and struggles have never been faced by humanity before, however. The Spanish Flu which took place after World War One and the Black Death that was rampant in Asia and Europe in the 14th century quickly come to mind as examples of past pandemics, but these are only two examples of devastating diseases throughout human history. The Plague of Athens that was raging during the beginning of the Peloponnesian War in 430 BCE is another such example. Though removed from our current situation by many centuries, its symptoms and the effects it had on the population of Athens have been meticulously recorded by the general and historian Thucydides, giving us the opportunity to compare his account to our own experiences today. The disease may be different, and the image he portrays may be more violent and desperate than our own, but nonetheless we can see similarities in how these two separate societies have reacted to unforeseen hardships. In this comparison, we can come to understand at once our own good fortune at going through a pandemic with the support of modern technology and medicine as well as how universal our reactions are to this type of suffering, thereby making it natural rather than shameful. Humanity has faced a great deal of diversity before, and COVID-19 will likely prove to be no different.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".