Privacy and anti-surveillance advocacy: the role/challenge of issue salience
Bibliographic record
Abstract
Purpose The proliferation of surveillance-enhancing laws, policies and technologies across African countries deepens the risk of privacy rights breaches, as well as the risks of adverse profiling and social sorting. There is a heightened need for dedicated advocacy and activism to consistently demand accountability and transparency from African states, governments and their allies regarding surveillance. The purpose of this paper is to understand the issue frames that accompany anti-surveillance and privacy advocacy in Ghana and the related implications. Design/methodology/approach Using a qualitative and interpretivist approach, the author focuses on three different surveillance-oriented incidents/programs in Ghana and analyzes the frames underpinning the related advocacy and narratives of various non-state actors. Findings Privacy and anti-surveillance advocacy in Ghana tends to be less framed in the context of privacy rights and is more driven by concerns about corruption and value for money. Such pecuniary emphasis is rational per issue salience calculations as it elevates principles of economic probity, transparency and accountability and pursues a high public shock value and resonance. Practical implications Economics-centered critiques of surveillance could be counterproductive as they create a low bar for surveillance promoters and sustains a culture of permissible statist intrusions into citizens’ lives once economic virtues are satisfied. Originality/value While anti-surveillance and privacy advocacy is budding across African countries, little is known about its nature, frames and modus compared to such advocacy in European and North American settings. To the best of the author’s knowledge, this is likely the first paper or one of the first dedicated fully to anti-surveillance and advocacy in Africa.
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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 | 0.008 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".