MétaCan
Menu
Back to cohort
Record W4380303349 · doi:10.5406/15351882.136.540.03

“Urgencies” in the Field: Three Perspectives

2023· article· en· W4380303349 on OpenAlexaff
Thomas Grant Richardson, Jon Kay, Maida Owens, Tim Frandy

Bibliographic record

VenueJournal of American Folklore · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFolkloreStewardship (theology)SociologyCreativityIndigenousHistoryMedia studiesAnthropologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Abstract Taken from a virtual presentation at the 2021 annual meeting of the American Folklore Society, three folklorists come together to present their ongoing work under the auspices of “urgencies of the field.” Jon Kay concerns himself with the urgencies of our temporal, corporeal bodies, in addressing creativity in older adults and offering suggestions for cross-pollination between folklore studies and gerontology and creative aging. Maida Owens focuses on climate change and the radical displacement of communities, turning to the concern of what happens to cultural traditions when the people of a community must relocate. Grounded in Indigenous approaches, Tim Frandy considers a decolonizing of our minds with real-world applications that guide us toward better stewardship of the natural world and better physical and mental health practices. Three folklorists, working within the intersectionality of public and academic spheres, and expanding the reach and impact of folklore's work, are finding ways to use their skills and knowledge to address unwelcome urgencies in our world.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.036
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0350.111
Scholarly communication0.0360.023
Open science0.0040.026
Research integrity0.0160.024
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.278
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of American FolkloreSame topicFolklore, Mythology, and Literature StudiesFrench-language works237,207