Bibliographic record
Abstract
Web-based interactive documentaries offer an innovative approach to reconstructing history, allowing users to explore historical content within a specific thematic context freely. This paper explores how transnational shared history, exemplified by World War I (WWI), is integrated into such documentaries, using the interactive documentary A Global Guide to the First World War (2014) as a case study. This documentary, a collaboration between the Guardian, historians, and the Imperial War Museum, employs interactive technologies and transnational historical narratives. It presents seven video chapters that allow audiences to explore WWI from a global perspective, going beyond the traditional single-narrative viewpoint. The interactive sections are based on a well-designed digital world map that provides users with diverse perspectives on the war, facilitating a broader emotional resonance. However, while ensuring authenticity, the documentary's use of authoritative narrative strategies tends to create a sense of alienation among viewers. It underscores the importance of incorporating personal narratives alongside official histories to foster deeper engagement and understanding. The paper argues for a more nuanced approach that balances the authoritative historical narratives with individual perspectives. This study demonstrates that the representation of transnational shared history and multiple perspectives is highly compatible with the interactive technology of web documentaries. The paper concludes that these digital platforms can effectively facilitate global understanding of shared historical events while encouraging critical and dialectical historical reflection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".