Varieties of an Atheist Public in a Digital Age: The Politics of Recognition and the Recognition of Politics
Bibliographic record
Abstract
With the rise of atheism as a cause célèbre in the last decade or more, media and others have offered many interpretations for the apparent growth of nonbelief, ranging from the apocalyptic to the utopian. Many cite the Internet as a major contributing factor to this growth; undoubtedly new media have provided atheism with greater visibility. In this article it is argued that atheism as an Internet phenomenon ought to be understood less as the manifestation of a social fact and more as the discursive constitution of one or more publics in Michael Warner’s sense of the term. To this end, the article draws attention to a body of data that has received limited attention in scholarship to date, namely the blogs of some notable atheists. These are limited to blogs originating in the United States, and especially those by authors who identify as ‘progressive’. Thus, the conclusions drawn are not imagined to apply outside that context, nor are the sources employed considered to be representative of American atheism. But these limitations present no bar to the analysis of the particular discursive practices of the authors in question. Following Warner, virtual atheism as a public or publics has little capacity for agency: even if its growth as a social fact is true, and even as it develops agendas for social change, it is neither discursively or substantively robust enough to challenge any aspect of the contemporary neo-liberal order.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.048 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".