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Record W4200295779 · doi:10.15353/cfs-rcea.v8i4.458

No syllabus, no problem

2021· article· en· W4200295779 on OpenAlexaffvenue
David J. Connell

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Practices and Policies
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsSyllabusPremiseRelation (database)Blackboard (design pattern)PedagogyProcess (computing)Mathematics educationSociologyEngineering ethicsPsychologyEngineeringComputer scienceEpistemology

Abstract

fetched live from OpenAlex

The intimate relation people have with food provides unique opportunities for teaching. In this field report, I will describe and reflect upon the method of student-centred learning I use in a first-year university course entitled Food, Agriculture & Society. The aim of the course is to provide students with a broad understanding of how food and agriculture have shaped society and can contribute to a more sustainable future. Consistent with food pedagogy, a premise of the course design is that the intimate relation students have with the food they eat reflects their personal values and responsibility for their choices. An innovative element of my approach is that I co-create the syllabus. The course starts by writing the word “Food” on the blackboard. I then facilitate a multi-step process with students to co-create the syllabus. For most of the course, students lead the preparation and delivery of lectures on their selected topics. In this report, after describing the course design, I reflect upon my approach in relation to the tenets of food pedagogy, as well as discuss student feedback and my experience of teaching the course.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.063
GPT teacher head0.320
Teacher spread0.257 · 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 designNot applicable
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

Citations1
Published2021
Admission routes2
Has abstractyes

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