Leveraging Visibility, Gaining Capital? Social Media Use in the Fight Against Child Abusers: The Case of The Judge Beauce
Bibliographic record
Abstract
This article examines the constitutive role of mediated visibility in the emergence of contemporary vigilante initiatives. Here, visibility is conceptualized as a “heuristic device” to understand social phenomena, as well as a lever for organizations to acquire various forms of capital. The article uses the case of The Judge Beauce—a Canadian organization created in 2015 to fight against child abusers—to understand how vigilante collectives can lever mediated visibility, and online visibility in particular, to acquire specific forms of policing capital (economic, social, political, and cultural). Results show that mediated visibility was indeed crucial for raising funds, constituting vigilant/e publics, and defining vigilante identities, relations, and practices. Yet, as a “double-edged sword,” mediated visibility brought on public scrutiny that simultaneously resulted in a series of liabilities. Finally, this article contends that vigilantism in the digital age should be defined as the enactment of power im(balances) through the instrumentalization of mediated visibility rather than considering force or the threat of its use as its main feature.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.036 | 0.028 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".