Bibliographic record
Abstract
: In this chapter, the director recounts the experience of creating Intravene , an immersive experience based solely on auditory storytelling around the opioid epidemic. Coming from the perspective of some with experience in film production, this chapter offers a ground-level look at the production of an audio-only immersive experience. In so doing, it raises question about the role that auditory stimuli play in fostering a sense of immersion in audiences. It also serves as a document of the making of Intravene , as it was written during—and after—the project's production. Keywords: immersive media production, opioid epidemic, Crackdown , Darkfield “Episode One: Benzodope” You put on the headphones and are asked to close your eyes. The signature Darkfield Radio bumper fades in: “Connecting… Please wait for a moment… Connecting… connecting… connecting. Darkfield Radio : no news, no music, no opinion.” There is a loud bang and the sound of water flowing. The dulcet voice of a robotic public address begins: Please take a seat and wait for your number to be called. We apologize for the delay, some of our staff are sick. Please be patient. For those of you who have not been here before, I can assure you, you are not dead, this is not purgatory … This room is impossible to imagine, it is a place of forgetting and a place of stolen time, it can be described only as a hole in those you have left behind. Calling overdose number 1,052. A woman's voice whispers in your left ear: “Wait here, I’ll get you a bundle.” A weave of documentary voices sets up the theme of the episode. Garth Mullins, the Executive Producer of Crackdown , recalls when he overdosed on a combination of benzodiazepines (benzos) and opioids and had two days of his life wiped from his memory. Dean Wilson, a longtime activist with the Vancouver Area Network of Drug Users (VANDU), talks about the ever more toxic supply of street drugs and insists we should stop calling them overdose deaths, people are dying of “drug poisoning.” Martin Steward, another activist with VANDU adds: “I know more people that have died than are still alive.”
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".