MétaCan
Menu
Back to cohort
Record W2947999181 · doi:10.15353/cfs-rcea.v6i2.255

Food Network’s food-career frenzy? An examination of students’ motivations to attend culinary school

2019· article· en· W2947999181 on OpenAlexaffvenue
Ryan Whibbs, Mark Robert Holmes

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsUniversity of GuelphGeorge Brown College
Fundersnot available
KeywordsPsychologyFood preparationMedical educationAdvertisingFood scienceFood processingMedicineBusiness

Abstract

fetched live from OpenAlex

This research presents the findings of a year long study, undertaken between 2016 and 2017, seeking to understand the degree to which students are influenced to attend culinary school by food medias, social media, and the Food Network. The notion that food medias draw the majority of new cooks to the industry is often present in popular media discourses, although no data exists seeking to understand this relationship. This study reveals that food medias play a secondary or tertiary role in influencing students to register at culinary school, while also showing previously unknown patterns related to culinary students’ intention to persist with culinary careers. Nearly 40 percent of this sample do not intend to remain cooking professionally for greater than five years, and about 30 percent are “keeping other doors open” upon entry into culinary school. Although food celebrity certainly plays a role in awareness about culinary careers, intrinsic career aspirations are the most frequently reported motivation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.241
Teacher spread0.189 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Food Studies / La Revue canadienne des études sur l alimentationSame topicCulinary Culture and TourismFrench-language works237,207