Understanding government discourses on social media: Lessons from the use of YouTube at local level1
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
Local Governments around the world have taken advantage of social media during the past ten years to improve transparency and to provide public services. Challenges related to information management and citizen participation have emerged, namely at the local level where the diffusion of social media has been slower compared to initiatives launched at the national level. This paper analyzes how the use of social media can reflect a change in the discursive exchanges established between local governments in Canada and Mexico and citizens. To achieve this goal, the use of YouTube by the municipalities of Quebec and Morelia was examined by using digital methods and content analysis. The author proposes the emergence of new conditions between government and users, which are changing the discourse, identity, and communication purposes of the municipalities. However, the development of more dialogic communication processes supported by social media is still a promise, at least on YouTube.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it