MétaCan
Menu
Back to cohort
Record W2889872946 · doi:10.18432/ari29378

Too Subtle for Words: Doing Wordless Narrative Research

2018· article· en· W2889872946 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeEmbodied cognitionStorytellingPresentation (obstetrics)PsychologyNarrative inquiryAestheticsVisual artsArtLiteratureEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Inspired by the wordless novels of early twentieth century Belgian artist Frans Masereel, this paper introduces wordless narrative research, a dynamic method of inquiry that uses visual storytelling to study, explore, and communicate personal narratives, cultural experiences, and emotional content too nuanced for language. While wordless narrative research can be useful for exploring a range of social phenomenon, it can be particularly valuable for exploring preverbal constructions of lived experiences, including trauma, repressed memories, and other forms of emotional knowledge often times only made accessible through affective or embodied modalities. This paper explores the epistemological claims of the method while describing five considerations for doing wordless narrative research. The paper concludes with a presentation of an excerpt of There is No (W)hole (Horwat, 2015), a surreal wordless autoethnographic allegory, as an example of wordless narrative research.

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.

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)0.058
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.005
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.809
GPT teacher head0.745
Teacher spread0.064 · 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