Multilingual Essay Mills: Implications for Second Language Teaching and Learning
Bibliographic record
Abstract
Considering increased availability of online companies offering academic work in a number of languages, we conducted a rapid review of websites which might offer online contract cheating (e.g. “essay mills”) to better understand how prevalent these services are in additional languages and to what extent they are available to K-12 students. Our results included eighteen online sites offering academic work in ten languages: Arabic, English, French, German, Hebrew, Italian, Latin, Mandarin, Portuguese and Welsh. Two thirds of the websites marketed directly to K-12 students, with one offering explicit services to students in grades six and up. A resulting implication is that K-12 second language teachers need to be aware that such online services are available to their students and take steps to enhance academic integrity among young and adolescent learners. Keywords: Contract cheating, essay mills, second language, Canada, K-12 Note: The Alberta Teachers Association (ATA) is the publisher and copyright holder of this article. It is shared in this repository with their permission.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".