Discussion aspects of interdisciplinary interaction of journalism and oral history
Bibliographic record
Abstract
The article presents the context of modern scientific debates on the boundaries of interdisciplinarity. The subject of the study is the common procedure of the use of oral history practices in the mass media space. The oral history itself is changing rapidly under the pressure of digital platforms such as StoryCorps (USA), Listening Project (UK), The Story Project (Australia), and The Tale of a Town (Canada). Another key thing is the fact that the changes affected not only the technological process of archiving and dissemination of information but also the basic foundations of oral history, which is its methodology. The in-depth interview is replaced by the “rapid response collecting” method and historical storytelling. The purpose of the article is to outline the discussion field of the modern scientific discourse of the problem, to present the most significant interdisciplinary interaction using the example of world and Ukrainian media, namely: coverage of contradictory and ambiguous interpretations of historical facts; narrative; prolonged communication; multimedia and multiplatform. The research methods are traditional empirical methods of observation and description, as well as paradigmatic analysis of the functional features of oral history practices in journalism. Results of the research. Basic characterological directions proposed in the study allowed us to present the main points of discussion in various aspects: the use of oral historical materials, especially “hidden history” through the eyes of eyewitnesses, become an additional source of journalistic clarifications, investigations and expansion of the information agenda; addressing marginal themes of history, giving a voice to terrorist groups and participants in genocides poses extremely complex and ethically controversial questions to the audience; multimedia and multiplatform give new life to oral history information, while performance, theatre and participation are added to the usual practices of new media. The most expressive manifestation of changes in this interdisciplinary discourse is the practice of digital storytelling; its media use is illustrated by the BBC’s Capture Wales digital storytelling project. As part of the scientific discussion that has continued for the last few years, the issues of democratization of history, mass inclusion in digital archives, the creation of powerful social projects, and attempts to distance oral history as a separate discipline have been actualized. Moreover, it is recognized that, like any creative practice, interdisciplinarity remains a wide field for experimentation and creativity.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".