<i>“The Time That Is Left Us”</i>: Imagining a (Post)Pandemic Future and Plagued Temporalities in Michael Bay and Adam Mason’s <i>Songbird</i>
Bibliographic record
Abstract
Released during the height of the pandemic, Songbird (2020) received negative criticism from film critics for opportunistically capitalizing on the latent anxieties borne from those uncertain times. Critics have suggested that it sent an irresponsible message by emphasizing the capacity of public health institutions to enable authoritarian regimes. There is, however, critical and cultural value in confronting this problematic cinematic text during the (post)pandemic present as it can potentially allow a rethinking of how we conceptualize temporalities vis-à-vis film aesthetics and narrative. Songbird articulates a dystopian future where COVID-23 has ravaged the world and operates on two temporalities that are emblematic of the tension between the homogenous time of the authoritarian state and the ephemeral time of the people. By positioning the film as an example of what Giorgio Agamben calls “gestural cinema,” I examine how the film seeks to capture the irreconcilability of irrecoverable temporalities and the nostalgic future. The film dramatizes these temporalities in the context of a dystopian world where those infected with the virus are excluded in quarantine facilities while the remaining uninfected populace is forced to stay at home at all times with only a few exceptions. This article theorizes “plagued temporalities” as a new viral modernity that elicits a fresh, altered perception of chance and contingency. In Songbird, these plagued temporalities are experienced by the COVID-23 immune protagonist who can roam freely through urban spaces in solitude while simultaneously encountering figures who have different experiences of lived time.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".