Contract Cheating 101
An Exposé about the Industrialization of Academic Dishonesty,
and an Impending Thinking CrisIs.
Advocates of student loan forgiveness protest outside the Supreme Court. Kent Nishimura/Los Angeles Times/Getty Images. https://www.cfr.org/backgrounder/us-student-loan-debt-trends-economic-impact
Head office of Axact, an essay mill and fake diploma “giant”. https://www.nytimes.com/2015/05/18/world/asia/fake-diplomas-real-cash-pakistani-company-axact-reaps-millions-columbiana-barkley.html
Academic writer Langat in his house in Kericho country, Kenya, May 4, 2023. Thomson Reuters Foundation/Dominic Kirui.https://www.context.news/ai/why-pay-ghost-writers-in-kenya-when-ai-can-do-your-essays
From billions loaned in student debt, to millions spent on cheating on the Internet…what EXACTLY is happening?
About Contract Cheating 101 / Synopsis
As academia is currently struggling to coherently grapple with the gap between the consumer facing economics of Large Language Models (LLMs) and the governance facing process of awarding degrees and certificates – the key unknown for decision makers, educators and regulators in this new forming equation is the impact of the AI avalanche on public intellect and the modern student.
Unsurprisingly, it is hard to get students to open up about how they are using AI – and more importantly why and when they are using it – and to what end? Through this blog, you have access to something otherwise unavailable: what students do when they need help.
If you work in the field of higher-education, and are interested in this problem, this blog aims to give you a fresh prespective from the eyes of an outsider looking in. Perhaps the biggest challenge those working in higher-ed have right now, is deciding to how to ‘control’ the use of AI in classrooms – and the biggest challenge within that challenge is learning more on how students are actually using AI in classrooms.
I may not know a lot of things, but I have some inklings on the above. Since, well, long before ChatGPT, I was their ChatGPT. I wrote around 2-5 papers (anywhere between 4-16 pages) every week for around 5 years – and in total might have written more than 500 papers / 2,000 pages for other people as a “job”.
Some of my clientele have graduated to work in prestigious hospitals, law firms, marketing agencies, and other ‘honorable’ places of employment.
This blog series, hence, is your ‘backstage pass’ into the essay milll industry. It is an insider’s perspective of the industry, from a proxy author who wrote more than 300 papers during his ‘career’.
As educators, you probably have seen one side of your students: this blog series brings light to the second. Through screenshots, memoirs, diagrams you will learn how essay mills operate: how they market to students, their internal network, order distribution, what and how students communicate with writers, learn to identify ‘cheater’ archetypes and most importantly examine the nature of the problem with a more bird’s eye view.
Contract Cheating 101 is compiled to arm educators with knowledge. As we’re on the brink of a new age, where learning needs crucial re-designing perhaps I thought this experience will help. Hopefully, it will inspire not only technological change, but also pedagogical change.
Hopefully, by the end of this book you will have a working model of the contract cheating industry in your mind, and learn more about student behaviour and motivations and their relationship with their own education.
Hopefully, you can use that working model to aid your decisions pertaining to addressing contract cheating and/or relevant protocols in regulating usage of AI in classrooms – and perhaps introspect the role of education today and in the future.
Contract Cheating 101 is divided into three sections:
- A Manual: Contains details of the process and analysis of “cheating” behaviour which result in the academic dishonesty economy.
- A Dataset: The dataset contains around 1,100 actual orders from the essay mill I used to work for.
- A Memoir: Provides more exposition and narrative to the two above. It is written in a stream of consciousness style of writing – since interested parties have expressed interest in learning more about the writers behind the papers.
Knowledge is power, and with contract cheating 101 consider yourself armed.
Section 1: The Manual
The manual is a summary of 5 years of acquired experience in writing papers for students.
01
Inside an essay mill operation: two month’s worth of orders.
How many orders does a essay mill get per day? What academic level coursework gets outsourced the most? Learn the answers to these questions using actual orders placed by students.
04
Levels of collaboration, and trust graph.
We will generalize the process of collusive plagiarism and study relationships via trust graphs.
07
Why do students cheat?
This chapter explores the motivations of students, discusses discovered cheater archetypes and attempts to measure predicatibility of a student cheating using the MPC framework.
10
Impact of AI on academic integrity and writing pedagogy.
This chapter explores the social cost of AI.
02
Defining terminology.
What we decide to name things, affects the way people think about the said thing.
05
The cheating economy.
Exploring the cheating problem as a demand and supply problem.
08
Pedagogical detection and intervention in student authorship.
A long-form discussion and critique of “detection” methods on their long-term impact on student cognition.
03
Lifecycle of a ghost-written paper.
Learn how a ghost-written paper arrives on your desk – leaving behind no evidence.
06
Review of scholarly work on academic integrity.
Review of published work on contract cheating, and comparing how close they are to reality.
09
Enhancing cyber security in education information systems.
A short read on how “passwords” are fundamentally flawed in information systems designed to grant degrees.
This is still a work in progress, and updated bi-monthly.
If you find the material interesting, please consider subscribing 🙂
Section 2: Dataset
~1,100 actual orders from an actual essay mill. The dataset contains the following data of each order:
Anonymized
No personal details of the students – cause those generally aren’t shared with orders anyway.
Paper Deadlines
The number of days a student requested the paper to be returned in.
Number of pages
The number of pages ordered by the student.
Paper Topic
The subject the paper was ordered on.
Order Deadlines
The academic discipline of the paper.
Paper Instructions
The details about the paper the student shared.
Price
The amount paid to ghostwriters.
1,100 actual orders
Section 3: Memoir, The people behind the papers.
Today, when machines can hold a better conversation than an average human can. Now, perhaps, is a crucial time to revisit the role of writing and words in society: not only as recreations of symbols in bits and bytes but also as where those symbols come from: encapsulations of human experiences preserved in time.
I have been hesistant to write this, since everything I’ve seen and witnessed looked too normal, uneventful and boring to be ever commited to writing.
It wasn’t until a dear friend introducted me to the work of James Baldwin, and I realized that one person’s mundane is another person’s impossible: no matter what I do I can never experience how it felt like to be a African American in Harlem in the era of the Civil Rights Movement.
The people I have discussed this with, have likened it to Frank Abegnale’s Catch Me If You Can – in practicality though – is an extension to Dave Tomar’s Shadow Scholar and adds more light, shade and a different context from a different lived life.
To avoid these works not subtly influencing mine, I have not read them – though I plan to read Tomar’s work once I am done. Mainly to reconcile our experiences over both sides of the Atlantic.
Additionally, data is the lifeblood of decision making, but often, in the social sciences we tend to forget that people are not particles. The ‘data’ we create is not caused by universal laws, but a result of emotion, situation and circumstance – the essence of which is quite difficult to capture numerically.
Therefore, in human matters, sometimes the exposition on how that data was produced provides insights as well.
Overall, it is a compilation of thoughts, reflections and personal notes on the inter-relationship of capitalism, modernity, education, morality, technology, pedagogy, immigration and income inequality.
Through these multiple lenses, you and I, together question the illusion of progress and global society’s relationship with knowledge.
