Broadcasting Reform in Canada: The Case for a Georgist View of the Audience Commodity
Bibliographic record
Abstract
Background: The Government of Canada’s Online Streaming Act attempts to incorporate online streaming services into the “single system” of the Broadcasting Act. The legislation has been heavily criticized for a variety of reasons, and constructive debate has been hampered by the lack of a clearly defined policy rationale or public interest objective—in large part because the term “broadcasting” is ill-defined in the internet context. Analysis: This article applies Georgist political economy to reinterpret Dallas Smythe’s concept of the “audience commodity” for the purpose of integrating emergent theories about the economics of attention and freedom of speech in the context of broadcasting and online media regulation. The principal argument is that a resource-centric view of human attention creates a technology-neutral conceptual basis for determining the scope of what is and is not media broadcasting. Conclusions and implications: The conceptual framework developed aligns the audience commodity concept with the contemporary business reality of content creators and helps draw some defining lines around the concept of “broadcasting” in the era of Internet platforms. Transitioning the fundamental basis for the definition of “broadcasting” from one of transmission methods to one of controlling the bottlenecks of attention would make it far easier to construct meaningful legislation in the public interest.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.020 | 0.028 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".