Bibliographic record
Abstract
The genesis of this edited volume came out of a conference, “Contours of Film Festivals Research and Methodologies,” which was originally conceived to be a one day in-person gathering in London in March 2020 which turned out to be the day when the first COVID-19 lockdown was introduced in the UK. As airplane tickets, hotel bookings, and dinner reservations were being canceled we announced that the conference would be postponed until September 2020. In a swift gesture that felt quite radical at the time, we decided to embrace what was a new format for an academic event and deliver it as a virtual conference via Microsoft Teams and Zoom. Almost immediately this format began to bear fruit as it allowed us to open up and expand the conference in new and unexpected directions. We were observing first-hand and by happenstance how any new format to produce and to disseminate knowledge is bound to create its own public which didn’t exist before ( de Mourat, Ricci, and Latour 2020 , 103). Firstly, we realized that we were able to include many more conference speakers than our original conference budget would ever have allowed us to do. Secondly, we noticed that the reach of our conference became much greater as with the virtual format we were able to attract audiences far beyond London and the UK, and not just from the Global North but also from the Global South. Our online conference included audience participants from the US, Europe, Canada, Tanzania, Chile, Pakistan, and other countries. Attending were not only film festival scholars who formed part of various networks such as FFRN (Film Festival Research Network), but also colleagues from NECS (European Network for Cinema and Media Studies), SCMS (Society for Cinema and Media Studies), and other scholarly associations. Thirdly, among the new roster of panelists and audience participants, there was a much higher proportion of film festival programmers of whom few would have been able to attend the original in-person conference in London. They were film programmers, archivists, curators, film festival directors (former or current), or else faculty who could be considered “hybrid” scholars and practitioners (that is, faculty who also founded or ran a film festival, or film festival programmers who had graduate degrees in the arts who left academia for the film festival world). Their participation changed the character of the original event radically, and ultimately inspired the direction and format this edited volume eventually took. We focused our investigation on exploring practice-based research in relation to film festivals and decided to publish the work as open access.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.536 | 0.346 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".