Bibliographic record
Abstract
The 11-minute VR film Border Sounds takes the viewer on a journey across an invisible line that separates Northern Ireland from the Republic of Ireland through haikus and sounds by people who live near this line. These stories were captured during a collaborative outreach program by the official archive for Northern Ireland, PRONI (Public Record Office of Northern Ireland), and the creative media hub Nerve Centre in 2021. This reflective practice-led research examines the filmmaking process, particularly how digital technology was used to engage with people remotely and make a film in a participatory way: to what extent can digital technology, such as Zoom, make filmmaking more accessible to rural people? What role can participatory filmmaking play in post-conflict storytelling? I also discuss the strengths and limitations of virtual reality as a storytelling format – does it really offer a more immersive experience? Are there any access barriers? Is it the most adequate medium to tell stories about the border, particularly in sensitive contexts such as Northern Ireland? I argue here that while virtual reality technology enabled Border Sounds to offer a unique on-screen experience of the Irish Border, it also has limitations in terms of audience reach, long-term preservation and access.
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 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".