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 Political economy of the media includes several domains including journalism, broadcasting, advertising, and information and communication technology. A political economy approach analyzes the power relationships between politics, mediation, and economics. First, there is a need to identify the intellectual history of the field, focusing on the establishment and growth of the political economy of media as an academic field. Second is the discussion of the epistemology of the field by emphasizing several major characteristics that differentiate it from other approaches within media and communication research. Third, there needs an understanding of the regulations affecting information and communication technologies (ICTs) and/or the digital media-driven communication environment, especially charting the beginnings of political economy studies of media within the culture industry. In particular, what are the ways political economists develop and use political economy in digital media and the new media milieu driven by platform technologies in the three new areas of digital platforms, big data, and digital labor. These areas are crucial for analysis not only because they are intricately connected, but also because they have become massive, major parts of modern capitalism.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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