Mapping the Intersection of Two Cultures: Interactive Documentary and Digital Journalism
Bibliographic record
Abstract
The convergence of digital journalism and interactive and participatory documentary, two forms at the defining edges of their respective fields, is the focus of this report. Why interactive and participatory documentary? Because these immersive, visual and, above all, experimental narratives have developed rapidly over the past few years, offering wide-ranging examples for journalists who seek to reach new audiences, to enhance the relevance of their reporting for an informed, engaged citizenry, and to make better use of the interactive and collaborative potential of today's mobile technologies.This report contextualizes and maps the views of the people who are leading change, charting their ambitions and concerns, tracking their organizations and strategies, and interpreting the larger patterns that emerge as storytellers and producers redefine their arts. It considers such institutional imperatives as reorganizing the production pipeline and means of distribution, listening to and working together with audiences, partnering with other media organizations, and looking to internal assets such as archives.Case studies drawn from organizations such as The New York Times, The Guardian, National Film Board of Canada, NPR, AIR, Frontline, and other sector-leading organizations examine change within particular institutions, as well as alliances between them and the production and distribution of particular joint projects. A broader environmental assessment of the conditions faced by legacy journalism organizations complements and situates the case studies. Against this backdrop, the case studies illustrate innovations and opportunities that have recently emerged at the intersection of journalism and documentary, charting best practices as well as lessons learned that can help quality journalism thrive in this fast-changing ecosystem.
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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 | 0.020 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.011 | 0.046 |
| Scholarly communication | 0.035 | 0.028 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".