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Record W4214821696 · doi:10.1007/978-3-030-83255-1_10

Pay-To-Pass: Evolving Online Systems That Undermine the Integrity of Student Work

2022· book-chapter· en· W4214821696 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEthics and integrity in educational contexts · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsUniversity of Calgary
FundersUniversity of Guelph
KeywordsCheatingAcademic integrityContext (archaeology)Work (physics)Reflection (computer programming)Public relationsInternet privacyPsychologyEngineering ethicsPedagogyMedical educationBusinessPolitical scienceSociologyComputer scienceEngineeringSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Abstract In an age where information is available at our fingertips, students in the post-secondary environment have equally ready access to resources that can be supportive of their academic development or academically questionable. In this chapter, we describe the pervasiveness of pay-to-pass websites in the Canadian post-secondary context. We distinguish pay-to-pass websites from other forms of contract cheating by defining them as sites encouraging students to share and access course material, assessments, and notes for academic and personal gain, as well as those providing real-time academic support. This chapter is a reflection on the nature and impact of these sites and explores a three-pronged approach to addressing the challenges posed by them on the upholding of academic integrity in post-secondary education.

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)0.010
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.023
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 head0.133
GPT teacher head0.402
Teacher spread0.269 · 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