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Record W3094654390 · doi:10.15402/esj.v6i1.68231

Participatory Ethnographic Film: Video Advocacy and Engagement with Q’eqchi’ Maya Medical Practitioners in Belize

2020· article· en· W3094654390 on OpenAlexafffundvenue
James B. Waldram

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Saskatchewan
KeywordsMayaEthnographyCitizen journalismFilmmakingSociologyRepresentation (politics)Visual artsMedia studiesAestheticsPublic relationsPolitical scienceArtHistoryAnthropologyArchaeologyMovie theaterLawPolitics

Abstract

fetched live from OpenAlex

There continues to be significant debate about what constitutes an “ethnographic film.” Contemporary standards for production require large budgets and sophisticated film crews, and as a result marginalizes those films produced at the local level designed to meet local needs. This article documents the process of creating a participatory ethnographic film at the behest of a group of Q’eqchi’ Maya medical practitioners in Belize. From conception through to the approval of the final cut and distribution, the project was directed by the practitioners and executed on a shoestring budget and ‘in kind’ contributions. I argue that the genre of ethnographic film must accommodate local level aesthetic sensibilities about what constitutes a “good” representation of cultural issues, and consider the nature of the intended audience, thereby allowing space for a collaborative filmmaking process attendant to the world of the participants rather than that of international film festivals.

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)0.900
metaresearch head score (Gemma)0.852
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.9000.852
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.3210.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.648
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 head0.667
GPT teacher head0.602
Teacher spread0.065 · 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; both teacher heads agree on what is shown here.

Study designQualitative
DomainMethods
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
Published2020
Admission routes3
Has abstractyes

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