Digital Colonialism and the Role of Local Intermediaries: Examining Big Tech’s Impact on Data Sovereignty and Human Rights in Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article explores digital colonialism in Africa, focusing on how Big Tech and local intermediaries perpetuate data exploitation, infrastructure dependency and algorithmic bias. Applying a Third World Approaches to International Law (TWAIL) lens, it draws parallels between historical colonialism and the modern digital economy, highlighting persistent power imbalances in data control and tech sovereignty. Multinational firms from the Global North extract and monetise African data with little benefit to local communities, reinforcing dependency. Local actors (governments, tech elites and influencers) often enable this through policy gaps and cultural alignment with Western platforms. The article examines the impact on data sovereignty, human rights and economic autonomy, including risks of surveillance and silencing local voices. It calls for policy reforms, investment in African tech ecosystems, digital literacy and robust regional regulation. Ultimately, it advocates for digital justice and self-governance to reclaim Africa’s digital future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it