A retrospective: navigating and representing the lockdown in Jason Farries’ <i>Homesick</i>
Bibliographic record
Abstract
This interview attends to an earlier period in the COVID-19 pandemic. I discuss, with actor-director Jason Farries, the experience of making a film during the pandemic, what he hopes to say about it with Homesick (2021), and how it forms part of an emerging genre. Homesick follows the experiences of The Student (Farries), who is living in isolation and who has tested positive for COVID-19. Things do not improve for The Student as he loses power and as he becomes more disconnected than ever from his loved ones and from the wider world. Farries’ earlier work includes an adaptation of J. B. Priestley’s classic An Inspector Calls (1945), which is now available on YouTube, and which, at the time of writing, has been viewed more than 2.3 million times. Much has changed and much continues to change during the ongoing pandemic. The following interview contributes to research on creative industries by revealing the affordances and challenges of filming during its early days; by showing how Farries, through his project, compiles a range of different responses to and develops his own position on the lockdown; and finally, by providing some ways for reading its ending.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".