Consent: Objectivity and the Aesthetics of Re-enactment in Locative Audio Journalism about a Sexual Assault Trial
Bibliographic record
Abstract
Consent – walk the walk, a geo-locative audio documentary walk in St. John’s, Canada, explores a 2017 sexual assault trial that led to days of protests in the Newfoundland city: an on-duty police officer is charged with sexually assaulting an intoxicated woman he drove home from the town’s nightclub precinct. Producers Chris Brookes and Emily Deming’s work of ‘landscape journalism’ was designed to highlight the tension between popular and legal understandings of the term ‘consent’ in sexual assaults. While the audio walk is a compelling place-based listening experience, Consent raises issues around the impact of dramatised re-enactment in the documentary field, and the role that sound design treatment can play, in affective influence over the audience’s response. To protect the identity of the assault victim, the producers were not permitted to use the court audio recordings, so they employed actors to perform the court transcripts. While the original trial acquitted the police officer, the Supreme Court of Canada in 2019 has ordered a re-trial on the grounds the trial judge erred in directing the jury. This article explores the design choices and the aesthetic, ethical and legal challenges faced by the audio walk’s producers in applying journalistic concepts of objectivity and balance.
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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 | 0.019 | 0.033 |
| 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 | 0.020 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".