MétaCan
Menu
Back to cohort
Record W3173769601 · doi:10.18357/kula.133

Tribesourcing Southwest Films

2021· article· en· W3173769601 on OpenAlexvenueno aff
Melissa Dollman, Rhiannon Sorrell, Jennifer L. Jenkins

Bibliographic record

VenueKULA knowledge creation dissemination and preservation studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamRedressNarrativeFilm directorMedia studiesCitizen journalismMeaning (existential)Visual artsSociologyHistoryArtPolitical scienceLiteratureMovie theaterLawPsychology

Abstract

fetched live from OpenAlex

As a work in progress, the Tribesourcing Southwest Film Project seeks to decolonize midcentury US educational films about the Native peoples of the Southwestern United States by recording counter-narrations from cultural insiders. These films originate from the American Indian Film Gallery, a collection awarded to the University of Arizona (UA) in 2011. Made in the mid-twentieth century for the US K–12 educational and television markets, these 16 mm Kodachrome films reflect mainstream cultural attitudes of the day. The fully saturated-color visual narratives are for the most part quite remarkable, although the male "voice of God" narration often pronounces meaning that is inaccurate or disrespectful. At this historical distance, many of these films have come to be understood by both Native community insiders and outside scholars as documentation of cultural practices and lifeways—and, indeed, languages—that are receding as practitioners and speakers pass on. The Tribesourcingfilm.com project seeks to rebalance the historical record through collaborative digital intervention, intentionally shifting emphasis from external perceptions of Native peoples to the voices, knowledges, and languages of the peoples represented in the films by participatory recording of new narrations for the films. Native narrators record new narrations for the films, actively decolonizing this collection and performing information redress through the merger of vintage visuals and new audio.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.072
GPT teacher head0.412
Teacher spread0.340 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueKULA knowledge creation dissemination and preservation studiesSame topicRadio, Podcasts, and Digital MediaFrench-language works237,207