Bibliographic record
Abstract
Visiting family last summer I was surprised to spot the amount of red, blue and gold fabric – yes, Tibetan flags – flying from the roofs of village homes in the French Alps, something of a solidarity I guess with high altitude brethren at the other end of the Eurasian expanse. A little of Tibet in France. After the Olympic torch events of last year, why not. But then that did not prepare me for reporter Edward Cody’s piece on France in today’s Washington Post.\n“French Workers Return to Streets in Protest” predictably reported that a million-plus French were pounding pavement to shake Sarkozy out of his cautious, unsympathetic leadership in the face of jobs hemorrhaging around the country. No surprises there. Then:\n“Despite the rancor on their banners, most marchers seemed cheerful in the spring weather as they marched and shouted anti-capitalist slogans. They moved past the house where Gustave Flaubert, author of “Madame Bovary,” lived in the 19th century; they walked by the Kunga Tibetan restaurant, from where three Tibetans peered out at a raucous phenomenon that their countrymen left behind under Chinese rule were unlikely to witness any time soon; and they spilled into the Place de la Bastille, where street protesters kicked off the French Revolution in 1789 by tearing open a royal prison tower.”\nWow. Non sequitur extraordinaire. Where did that come from? I tried to follow the train of thought: Reference French literary giant. Reference launch of French Revolution. Reference China’s stranglehold on Tibet. Huh? Talk about conditioned synapses. Maybe predict that workers in the world’s third largest economy – China – might not be commanding the streets in protest “any time soon.” But Tibet?\nI guess all (mental) roads these days do lead to Lhasa.
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 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.006 | 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 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".