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chethanjs
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chethanjs
Hi guys,

I am getting paranoid.

One of my recommenders borrowed my macbook to do finishing touches on my recos before uploading them on the school's website.
Do the adcom people track ip addresses of the person uploading? Since Microsoft Word has Author information on it, will they think that I edited the recommendation and deny my application? :-(

I appreciate any inputs from people who worked with Admissions panel before.


Thanks guys.


Did he actually submit the letter on your laptop? If so, that could be a problem. Otherwise, I wouldn't sweat it.
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If you're worried about it, which is sounds like maybe you should be based on the above responses, then just call or email the admissions team explaining the situation. Remember, these are people on the other end, and my experiences with them is that they've always been very understanding of different circumstances and situations that arise during the application process. Don't stress!
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There's no need for adcom to manually verify anything. In today's age, don't you think it would be automatic? For instance, just a note that runs at the top of your application that automatically highlights anything odd. There are companies that already offer this kind of thing... check out the bottom of this: https://technolutions.com/slate/advantage

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Fraud detection

Slate features a robust fraud detection system. By evaluating document metadata and login histories for applicants and recommenders, Slate is able to issue intelligent and adaptive alerts when potential fraud is detected. Our proprietary plagiarism detection system, able to be run on-demand or automatically on schedule, searches the entire corpus of uploaded documents and will identify statistically-significant duplication.
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QiuYidio
There's no need for adcom to manually verify anything. In today's age, don't you think it would be automatic? For instance, just a note that runs at the top of your application that automatically highlights anything odd. There are companies that already offer this kind of thing... check out the bottom of this: https://technolutions.com/slate/advantage

Quote:
Fraud detection

Slate features a robust fraud detection system. By evaluating document metadata and login histories for applicants and recommenders, Slate is able to issue intelligent and adaptive alerts when potential fraud is detected. Our proprietary plagiarism detection system, able to be run on-demand or automatically on schedule, searches the entire corpus of uploaded documents and will identify statistically-significant duplication.

Here's what I don't get about this. There are numerous instances where the recommender will share a similar IP address if you guys work in the same building or other cases where let's say the writer borrows your laptop to log in or cases like mine. Will all those be flagged as cases of "fraud?" Also, this software searches uploaded documents for cases of duplication. In many cases, we tell the recommenders what to focus on or talk about, such as certain projects or examples of leadership. We then talk about that in our essays to reinforce the message of the recommenders. Will those be flagged as "duplication" because we may have used the same stories or phrases? I don't know the answer to any of these questions. Just wondering.
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QiuYidio
There's no need for adcom to manually verify anything. In today's age, don't you think it would be automatic? For instance, just a note that runs at the top of your application that automatically highlights anything odd. There are companies that already offer this kind of thing... check out the bottom of this: https://technolutions.com/slate/advantage

Quote:
Fraud detection

Slate features a robust fraud detection system. By evaluating document metadata and login histories for applicants and recommenders, Slate is able to issue intelligent and adaptive alerts when potential fraud is detected. Our proprietary plagiarism detection system, able to be run on-demand or automatically on schedule, searches the entire corpus of uploaded documents and will identify statistically-significant duplication.

Here's what I don't get about this. There are numerous instances where the recommender will share a similar IP address if you guys work in the same building or other cases where let's say the writer borrows your laptop to log in or cases like mine. Will all those be flagged as cases of "fraud?" Also, this software searches uploaded documents for cases of duplication. In many cases, we tell the recommenders what to focus on or talk about, such as certain projects or examples of leadership. We then talk about that in our essays to reinforce the message of the recommenders. Will those be flagged as "duplication" because we may have used the same stories or phrases? I don't know the answer to any of these questions. Just wondering.

I think it's the combination of things. For instance, if the log-in is from the same IP, but the fraud detection doesn't find statistical similarities, then you're probably fine. But if the log-in is from the same IP, there's similar grammatical structure / diction, and the log-in times are one after the other, then it'll probably flag.
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