Netscapes of power: convergence, consolidation and power in the Canadian mediascape
Bibliographic record
Abstract
Grounded in a study of the Canadian mediascape, this article argues that trends toward media ownership consolidation are having a fundamental impact on broadcasting and the evolution of cyberspace as a whole. I argue that current trends reflect the rise of what we can call ‘Machiavellian media’ - communication and information systems saddled with three tasks: building the information society; populating cyberspace with workers/citizens/users; and projecting the ‘brand image’ of nation-states on a global plane. The article critiques the notion that new media, especially the internet, are disruptive technologies. Among other things, cyberspace is a class-divided space. More than this, though, networks - the basis of many ‘new media’ - are powerful entities and those who control them influence content providers’ access to people and people’s access to content. The article also analyzes three other factors that are affecting the evolution of networks and cyberspace: attempts to design ‘netscapes of power’, the privatization of cyberlaw, and ‘walled garden’ strategies. Together, these strategies seek to change the Internet into a mainly ‘read-only’ medium and to cybernetically integrate audiences, content and all organizational resources into a self-referentially enclosed information system governed by multimedia conglomerates’ need to defend their investments in a model of media evolution that has, at best, weak cultural foundations.
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.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.029 | 0.041 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".