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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".