MétaCan
Menu
Back to cohort
Record W4220794820 · doi:10.1080/14780887.2022.2047246

Carrying stories: digital storytelling and the complexities of intimacy, relationality, and home spaces

2022· article· en· W4220794820 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueQualitative Research in Psychology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsToronto Metropolitan UniversityUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsStorytellingDigital storytellingSociologyAestheticsAutoethnographyNarrativePsychologyEpistemologyGender studiesPedagogyArtPhilosophyLiterature

Abstract

fetched live from OpenAlex

Over the past decade, we have worked alongside storytellers to bring their stories into the world. These encounters have been challenging, exciting, and intimate. In this paper, we reflect on a digital/multimedia storytelling project in which we engaged with people who have experienced weight stigma in fertility, pregnancy, and motherhood care. We use the metaphors of story midwifery and surrogacy to describe the methodological-substantive interplay between what we do, how we do it, and what emerges in this (un)doing. In this reflexive and methodological paper, we engage with the affect and relationality of doing storywork. We reflect on and theorize around embeddedness, othering, belonging, power, shame, and joy in research encounters. Pragmatically, we consider how relational ethics combine with exhaustion and logistical challenges. Finally, we explore the tensions inherent to (co)producing stories at the boundaries of neoliberal academic temporalities and structures.

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)0.010
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.462
GPT teacher head0.634
Teacher spread0.173 · 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