Mapping Change in Canada’s Local News Landscape: An Investigation of Research Impact on Public Policy
Bibliographic record
Abstract
<p>This study investigates whether the Local News Map, a crowdsourced digital tool that tracks changes to local news outlets, influenced policy making that resulted in new government supports for Canadian journalism. It demonstrates how scholarly research informs government decision making and identifies a more nuanced approach to tracking research impact at a time when funders are increasingly demanding evidence that research dollars are well spent. We argue that research knowledge is used for various purposes at different points in policy making and that its impact should not just be assessed in terms of influence on a final outcome. Using a mixed-methods approach to chronicle opportunities for research influence, we found that map data were incorporated into news and social media content that helped push the news industry’s problems onto the government’s policy-making agenda. The data were also used by officials to understand what is happening to local newsrooms and to develop a policy rationale for government aid. The results suggest that when impact is defined as situations where scholarly knowledge raises consciousness of an issue, informs thinking or leads to the application of that knowledge, the result is a more realistic assessment of research impact on the policy process.</p>
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".