Democracy, Patriotism, and Schooling After September 11th Critical Citizens or Unthinking Patriots?
Bibliographic record
Abstract
From: The Abandoned Generation: Democracy Beyond the Culture of Fear reprinted with permission by the author I should like to be able to love my country and still love justice. I don’t want just any greatness for it, particularly a greatness born of blood and falsehood. I want to keep it alive by keeping justice alive. Albert Camus This is a difficult time in American history. The tragic and horrific terrorist acts of September 11 suggest a traumatic and decisive turning point in the history of the United States. Some commentators have compared it to the Japanese attack on Pearl Harbor. Others suggest that the history of the twenty-first century will be defined against the cataclysmic political, economic, and legal changes inaugurated by the monstrous events of September 11. Similarly, many people are now aware that, for better or worse, the United States is part of a global system, the effects of which cannot be completely controlled. There is also a newfound sense of unity organized not only around flag-waving displays of patriotism but also around collective fears and an ongoing militarization of visual culture and public space.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".