Blind Injustice: Theorizing Anonymity and Accountability in Modern Democracies
Bibliographic record
Abstract
Anonymity is one of the great enigmas in the history of Western philosophy. The possibility of acting anonymously – without fear of repercussions or accountability – can appear either as liberating or destabilizing, depending on the circumstances. Whereas anonymity is often lauded as a symbol of solidarity among activists, a source of protection for hackers and whistleblowers, and a small price to pay for genuinely free speech, other observers regard it with trepidation as encouraging rashness and abuses of power. Our goals in this article are two-fold. First, we aim to elucidate several dimensions of anonymity, including the variety of forms it takes as well as its potential uses and abuses. Second, we seek to develop a normative framework through which to evaluate contemporary cases in which anonymity plays a central role. Drawing upon several episodes from the history of political thought, we identify three factors relevant to assessing any particular claim to anonymity; we conclude with a discussion of anonymity’s role in campaign finance reform in the United States and anti-masking law in Canada.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.063 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".