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Record W4308698910 · doi:10.31468/dwr.975

Labour-Based Grading Contracts in an Indigenous-Specific Section of Academic Reading and Writing

2022· article· en· W4308698910 on OpenAlex
Loren Gaudet

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueDiscourse and Writing/Rédactologie · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGrading (engineering)IndigenousAcademic writingMathematics educationSociologyPedagogyPsychologyEngineering

Abstract

fetched live from OpenAlex

This essay outlines the experience of introducing a labour-based grading contract in a section of the University of Victoria’s standard introduction to academic reading and writing that was only open to students who self-identified as Indigenous. Labour-based grading contracts offer an alternative approach to conventional grading, in which a student’s grade is determined by the amount of labour that the student does over the semester. By emphasizing labour and learning, this approach to grading works towards decentering normalized whiteness in academic writing pedagogy. In this essay, I describe our labour-based contract, I explain how our class negotiated the contract, and I share some reflections on what went well and what I would do differently next time.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.145
GPT teacher head0.452
Teacher spread0.308 · 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