Crisis or Opportunity? Public Funding and Business Strategies of Italian Cinemas in the Face of Covid-19
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Covid-19 health emergency affected Italian cinema exhibition more severely than other industrial sectors: in the first lockdown alone, between March and May 2020, more than 4,000 screens stopped working and more than 6,000 direct employees being suspended from work; in the first quarter of 2020 alone, about EUR 120 million in box office was lost. A dramatic scenario that got worse in the following months, despite the brief interlude of reopening in the summer of 2020, but only following the observance of heavy and costly medical protocols. Throughout the year, debates and initiatives took place - involving policy makers, professionals, experts and cinephiles - aimed at concretely supporting cinemas and raising public awareness of the economic, but also cultural and social loss that the closure of these spaces has entailed. The Direzione Generale Cinema e Audiovisivo of the Ministry of Culture has set up, through an increasingly pressing succession of Ministerial Decrees, a Cinemas Emergency Fund to support companies, while the growth of streaming platforms has encouraged exhibitors to try their hand at creating online initiatives and virtual cinemas. Two years after the first forced closure of Italian cinemas, the paper intends to observe the state of health of the sector, which has been the subject of specific attention from the Italian government in the last two legislative periods. Through industry data and interviews, the paper will attempt to answer these questions: What impact did Covid-19 have on these cinemas? Was State intervention able to guarantee their survival? Which entrepreneurial strategies have the exhibitors put in place or should they adopt for the immediate future? And what social and cultural changes can be foreseen?
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it