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Record W2955195912 · doi:10.55612/s-5002-036-005

A food blog created by and for elders: a political gesture informed by the normative injunctions to eat and age well

2018· article· en· W2955195912 on OpenAlexaff
Maude Gauthier, Myriam Durocher

Bibliographic record

VenueInteraction design & architecture(s)/ID&A Interaction design & architecture(s) · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsNormativeSocializationSociologyPerspective (graphical)GesturePoliticsPublic relationsPsychologySocial sciencePolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

This article analyzes a food blog developed by and for elders. The organization under study developed this project to integrate itself in a mediatized food culture. Rather than to perpetuate the individualising processes that come with the pressure to eat, be, and age in a healthy way, the group members used food as a means to collectively work towards their ideals of social justice. They have done so by developing digital skills and by adding their voice to the mediatized food culture. Therefore, they gained visibility and created socialization spaces. Through this project, they challenge ageist conceptions of older people’s (non) uses of technologies as means to improve their health or to keep in touch with their children and grandchildren. The research is based on the researchers’ participation in the project and is rooted in a cultural studies perspective, drawing from the literature emerging from the fields of critical food and ageing studies.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0050.007
Open science0.0000.006
Research integrity0.0020.002
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 head0.038
GPT teacher head0.278
Teacher spread0.240 · 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 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

Citations7
Published2018
Admission routes1
Has abstractyes

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