The political economy of WikiLeaks: Transparency and accountability through digital and alternative media
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 The mainstream news media are expected to facilitate democracy by informing citizens, and holding corporations and governments accountable. This article demonstrates the uberization of the media through an analysis of WikiLeaks. Due to the complicity of the mainstream news media within the nation state – influenced by economic and political power relations – journalism becomes incapable of promoting this transparency and accountability, leaving those necessities to the public – and to alternative media platforms. Alternative media platforms such as WikiLeaks, which exist transnationally and are not beholden to one state, have the potential to fulfil journalism’s traditional role of transparency and accountability. We argue that the release of the ‘Collateral Murder’ video by WikiLeaks, and the surrounding events, is an example of how alternative media platforms uberify journalism through the dissemination of information, avoiding the barriers that limit mainstream news media and thus become journalism’s future. This draws into question the future development of journalism, in particular values and norms around accountability, transparency and bias, as digital leaking troubles relationships between journalism, various institutions and the public. As the ideologies of uberification continue to shape journalism, these values, norms and relationships of traditional journalism could be strengthened or may face new challenges and obstacles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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