Navigating the Digital Jungle: Social Media's Relationship to Journalism
Bibliographic record
Abstract
This thesis is an examination of the relationship between journalism and social media in 2022.It begins by exploring the current landscape of journalism in the digital age and to what extent the benefits of social media are being harnessed by journalists, and what can happen when social media is misused by journalists.It continues with analyses of interviews with eight practicing Canadian journalists on their experiences working with social media and their employers' expectations of them.This thesis maintains that, despite its downfalls, social media remains a valuable tool for reporters and newsrooms.It also recognizes that there is a significant gap in communication when it comes to the expectations of how social media should be used by journalists and how they are currently using it.It concludes with a proposal of emerging best practices and potential stipulations for the future implementation of newsroom social media policies.2 "Countries with the most Facebook users 2022," Statista, July 15, 2022,
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".