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Record W4241148123 · doi:10.1515/9781474419482

Female Agency and Documentary Strategies

2018· book· en· W4241148123 on OpenAlexaboutno aff
Boel Ulfsdotter, Anna Rogers

Bibliographic record

VenueEdinburgh University Press eBooks · 2018
Typebook
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Documentary evidenceDocumentary filmHistoryPolitical scienceSociologyArt historyArchaeologySocial science

Abstract

fetched live from OpenAlex

Examines the politics of female authorship in relation to contemporary documentary practicesThis book, like its twin volume Female Authorship and the Documentary Image, centres on pressing issues in relation to female authorship in contemporary documentary practices. Addressing the politics of representation and authorship both behind and in front of the camera, a range of international scholars now expand the theoretical and practical framework informing the current scholarship on documentary cinema, which has so far neglected questions of gender.Female Agency and Documentary Strategies centres on how self-portraiture and contemporary documentary manifestations such as blogging and the prevalent usage of social media shape and inform female subjectivities and claims to truth. The book examines the scope of authorship and agency open to women using these technologies as a form of activism, centring on notions of relationality, selfhood and subjectivity, and includes interviews with Hong Kong based activist filmmaker and scholar Vivian Wenli Lin and Spanish documentarist Mercedes Alvarez.ContributorsAnna Backman Rogers, University of GothenburgLinda C. Ehrlich, Writer, Teacher, EditorKerreen Ely-Harper, Creative Media Researcher and Filmmaker Kristopher Fallon, University of California, DavisCadence Kinsey, University of YorkCarla Maia, Centro Universitário UNALidia Merás, Film Historian and ResearcherAnna Misiak, Falmouth UniversityKim Munro, Filmmaker, Artist and Teacher Kate Nash, University of LeedsJohn A. Riley, Woosong UniversityMonica Titton, University of Applied Arts and at the Academy of Fine Arts in ViennaBoel Ulfsdotter, Independent Scholar Gail Vanstone, York University, Toronto

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.040
GPT teacher head0.267
Teacher spread0.227 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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