Journalism and Libraries: Collaborating to Build a More Equitable, Accessible, and Engaged Information Space
Bibliographic record
Abstract
As Canadian journalism continues to encounter underfunding, shuttering outlets, and low public trust, now is perhaps the best time for the field to explore more collaborative channels with other institutions. This research explores collaborations between journalism and libraries and the impacts they have on labour, civic engagement, and power. The CBC/Radio-Canada’s Collab initiative, and specifically the partnership undertaken by CBC and the Notre-Dame-De-Grâce Benny library in Montreal, Gem of an Idea, are used as a case study upon which the rest of this research is built. Using event observations, qualitative interviews and thematic analysis, this thesis aims to examine the ways in which collaborations can contribute to information spaces that are accessible and engaging for their community members. Further, this research uses the theoretical framework of critical pedagogy. Critical pedagogy is rooted in praxis and upholds the notion that all theorizing must eventually lead to action, which is best done through human interaction and reflexivity. As some critical pedagogists have pointed out, work that blends theory and practice create proactive spaces in which we might imagine new approaches to scholarship. The results of my study seek to broaden this discussion. The findings of this research paint an initial picture of the possibilities that can arise through collaboration as well as what it means for journalists, library staff, and, most importantly, the public.
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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 | 0.027 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.043 | 0.046 |
| Scholarly communication | 0.059 | 0.037 |
| Open science | 0.003 | 0.045 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".