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Record W6884652559 · doi:10.11575/prism/38945

Contract Cheating in Canada: How it Started and How it’s Going

2021· other· en· W6884652559 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCheatingSession (web analytics)LegislationAction (physics)Academic integrityContract management

Abstract

fetched live from OpenAlex

Purpose: The goal of this session is to provide an in-depth account of the history and development of contract cheating in Canada over the past 50+ years. You will also learn about the one and only (failed) attempt at legislation to make ghostwritten essays and exams illegal in Canada. Method: The content of this session is drawn from Eaton’s book chapter on contract cheating in the forthcoming edited volume, Academic Integrity in Canada: An Enduring and Essential Challenge (Eaton & Christensen Hughes) that involved over a thousand hours of historical research and digging into archival material to uncover that the contract cheating industry in Canada has been operating successfully for longer than most of us ever realized. Results: Get the details on a criminal case in the 1980s, noted as being the first of its kind in Canada, and possibly the Commonwealth, that made history when an essay mill owner and his wife were charged with fraud and conspiracy. The case was dismissed by the judge, leaving the contract cheating industry to flourish in Canada, which it has done with a vengeance. Then learn about an exposé in a major US magazine in the 1990s that presented in-details about the experiences of writers who supplied services to the contact cheating industry. Now that we are in the 21st century, find out what’s being done across the country today to take action against contract cheating. Implications: I share previously undiscovered evidence and insights that shows how the contract cheating industry has been proliferating in Canada for at least half a century. Even if you thought you knew about contract cheating in Canada, you’ll almost certainly learn something new in this session. I conclude with strong calls to action for educators, advocates, and policy makers.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.178
Teacher spread0.165 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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