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Record W4402740245 · doi:10.1177/13505068241280525

‘Make it look a little like a festival’: Film exhibition and festival organizing at <i>Films Femmes Méditerranée</i> during the COVID-19 pandemic

2024· article· en· W4402740245 on OpenAlexaff
Ylenia Olibet

Bibliographic record

VenueEuropean Journal of Women s Studies · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsExhibitionCoronavirus disease 2019 (COVID-19)PandemicFilm festival2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)ArtMedia studiesArt historyVisual artsHumanitiesSociologyVirologyMedicine

Abstract

fetched live from OpenAlex

This article attends to the strategies of survival, affective labour, and practices of care – for women’s film work and publics – within women’s film festivals during the COVID-19 pandemic through the case study of Films Femmes Méditeranée, a women’s film festival based in Marseille, France. The festival was founded in 2007 to give visibility to the work of female filmmakers from the Mediterranean through a curated program of films, showcased in art-house theatres, with free screenings for young audiences, students, the unemployed, and people living on social benefits. Drawing on interviews conducted with workers at Films Femmes Méditeranée, I first provide an overview of the history and the mandate of Films Femmes Méditeranée in relation to the legacy of early women’s film festivals by bringing to light the work of care carried on in the context of Marseille. I will then analyse Films Femmes Méditeranée’s practices of curation and care through digital media during the pandemic. Through a consideration of the labour of film programming and festival organizing vis-à-vis social distancing measures and an examination of curatorial choices, I interrogate how Films Femmes Méditeranée has adapted to the pandemic crisis through digital media to maintain its commitment to fostering transnational approaches to women’s film culture and to provide a space for encounters between female filmmakers and audiences.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.274
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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