Bibliographic record
Abstract
In Wikipedia and the Politics of Openness, Nathaniel Tkacz identifies and interrogates the political underpinnings of openness as it has come to be expressed in the twenty-first century.This pioneering critique is primarily a response to proponents of openness who commonly either ignore its political dimensions or claim it to be apolitical.Tkacz's primary goal is not to denounce openness but rather to demonstrate that "openness is politically fraught" (175) and to develop a theoretically rigorous vocabulary with which to address its politics.To expose the intrinsically political nature of openness, he selects the various elements that are most often considered integral to open projects and points out the politics of each in corresponding realworld examples, most being drawn from the early history of Wikipedia.The book's short conclusion asserts a connection between openness and neoliberalism, an ideology that Tkacz opposes but considers important to take seriously.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".