The News about the News : Exploring the Impact of Meta’s Social Media News Ban on the Quality and Quantity of Online News in Canada
Bibliographic record
Abstract
Little has been written about the effects that social media news bans (SMNBs) have on journalism and, as a potential consequence, democracy. This paper provides an initial assessment of whether SMNBs—in particular, those that are isolated to specific countries and social media platforms—incentivize online news organizations to shift their publication patterns in ways that could be detrimental to citizen participation in democracy. More specifically, an original dataset of Canadian newspaper headlines from before and after Meta’s 2023 SMNB is analyzed for correlations between the existence of an SMNB and the amount of sensationalized and foreign news published. The results indicate no observable effect on either outcome. Therefore, this study does not find that SMNBs pose significant consequences for the quality and quantity of domestic journalism in the sample examined. However, further research is necessary in order to determine what broader impact such bans may have on individuals’ capacity to make informed democratic decisions.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".