Science topic

Fraud - Science topic

Exploitation through misrepresentation of the facts or concealment of the purposes of the exploiter.
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It is the trending topic for a publisher this week.
I want to learn the opinion of Academia members. Is it due to environmental factors or personal over-ambition?
Why does anyone commit fraud?
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Dear Prof. Ferhan Kuyucak Sengur and all the respected RG colleagues,
This respected portal (i.e. RG) defines plagiarism as:
The term “plagiarism” has different meanings, but it usually includes copying somebody else’s work without permission.
On the other side, self-plagiarism is when the author republishes portions of his/her own previously written research work while authoring a new work.
I may be somewhat old-fashioned, but please have a look at the following golden principles on how to avoid plagiarism in academic writing, especially Self-Plagiarism:
  1. Never use the "Copy-Paste" trend: Use your own words instead of copying the words of others. Needless to say that if you are using your own words, then there is no chance of plagiarism accusing.
  2. Never repeat yourself: There are many re-published articles that are slightly or even considerably modified, and still not changed!
  3. If you have co-authors, just trust your words!
  4. If you use your own words, there should be no plagiarism issue. In turn, there is no need for the tools of plagiarism checking. Since there is no guarantee that the original content of your manuscript might not be copied and sold to others before it is published by you, I discourage using any free-software checkers for plagiarism; some of them are betrayers. Despite that offline ones are rare and if you are insisting to use anti-plagiarism software, offline checker programs are safer than online ones.
  5. In some cases, you can paraphrase the sentences in the original document. But don't forget to write a reference.
  6. You must always insist on honesty. Furthermore, you have to always remember that there should be a new added value.
  7. You must always insist on doing real research, not "Wikipedia" research.
  8. Do not put any of your research work anywhere until it is published and tagged with your name. Please wait until the paper is accepted and then published in that journal. Then, upload that research item on any platform you wish.
  9. Despite that offline ones are rare and if you are insisting to use anti-plagiarism software, offline checker programs are safer than online ones.
  10. In my opinion, most of the free-software-checkers for plagiarism don't work effectively. Unfortunately, you have to pay for the sake of getting good results.
  11. Try to develop your own style for the text writing.
  12. Try to read as much scientific literature as possible, especially in your own research field area.
  13. A reminder for all respected researchers: In order to maintain research integrity, plagiarism (الاستلال) has to be given up. However, many people do not know whether they are committing plagiarism intentionally or unintentionally.
Finally, believe me, or not: If you make one plagiarizing, you may solve one problem and fall into many others where some of which may be described as a knockout. Again and again, please always remember that if there were accusations of plagiarism, it is not well for any researcher's reputation, in any meaning.
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I am looking for a prediction of fraud in a company that would result in a percentage of the likelihood fraud could occur using both continuous and dichotomous independent variables. I am not looking for a binary regression with fraud or no-fraud as my dependent variable; the dependent would be a range in terms of percentage of fraud occurring in a company. Thank you.
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Yes. You'd use dummy variables (0 vs. 1) for the dichotomous predictor(s).
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I’m collecting survey data for for my Masters dissertation. I want to know whether remote working creates an opportunity for occupational fraud by measuring employees perceived effectiveness of their internal controls. Is this a prediction?
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Hi laj kol
The best method to detect impact qualitative method
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FORENSIC ACCOUNTING AS A TOOL FOR DETECTING FRAUD IN CORPORATE ORGANISATION
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Afriyie, S. O., Akomeah, M. O., Amoakohene, G., Ampimah, B. C., Ocloo, C. E., & Kyei, M. O. (2022). Forensic Accounting: A Novel Paradigm and Relevant Knowledge in Fraud Detection and Prevention. International Journal of Public Administration, 1-10.
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One of the main differences between Financial Audit and Forensic Audit is that the Financial Audit gives the guarantee that the financial statements that have been checked are true and fair and are reasonable whereas, Forensic Audit helps to analyze and investigate a certain set of transaction, if any fraud has been occurred.
The goal of this project is to set the record straight as much focus have been on the Financial Audit as the Fraud Detector.
The questions are: 1. Who then is the Fraud Detector, a Financial Auditor or a Forensic Auditor?
2. Why are Financial Auditors liable if failed in their audit duty to detect fraud within an organization?
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If the Financial Audit and Forensic Audit are distinct in their objectives, and the report from the Financial Audit may lead to a Forensic Audit, then why are Financial Auditors liable in cases of failure to unravel Frauds, in the case of the Arthur Andersen in the "Enron Scandal"? ...mind You, Arthur Andersen might have been reporting the Fraud Signals to the Enron Corporation Management for the need for a Forensic Audit but probably and deliberately they ignored the submissions/reports, however did they?
The Enron scandal was a series of events involving dubious accounting practices that resulted in the bankruptcy of the energy, commodities, and services company Enron Corporation and the dissolution of the accounting firm Arthur Andersen.
Arthur Andersen was only the Financial Auditor and not the Forensic Auditor I think so why their dissolution?
What are your views on this?
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For example, in supply chain or diagnostic, what is the importance of outlier or anomaly detection?
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Ever hear of quality control. An out of control point is an outlier. David Booth
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Difficult question, esp where scientists face persecution and harassment for whistle-blowing.
Could we have a Global body to report infringements to? A body with the power to investigate and prosecute?
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If there is no morality in everything, it is a worthless product. We Uzbeks have a saying: It is easy to be a scientist, it is difficult to be a man. Because it is very sad that even among scientists there are immoral people, which is primarily a sign of their lack of moral qualities.
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when make a study of corporate frauds and crimes , one notices always that corruption takes place when when one faces threat of punishment due to non compliance’s of laws .In india Satyam , Enron or ILFS are examples of corporate crimes arising out of non compliance’s .
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This article gives a broad overview of each of the four primary compliance risks in Vietnam: anti-corruption, regulatory compliance, employee fraud and corporate criminal liability. https://globalinvestigationsreview.com/review/the-asia-pacific-investigations-review/2020/article/vietnam-compliance-risks
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Manipulations of metrics take many forms, with new ones likely to emerge, but they all share some key traits because of the nature of the object they target: impact.
Editors increase their journal’s impact factor by entering into co-citation agreements with other journal editors, which involves having the authors of one journal cite articles from the colluding journal; some universities invite their faculty to cite each other to help improve the institution’s rankings; and other universities pay productive scholars from other institutions. The presence of fake collaborators also facilitates the publication and visibility of article thanks to the institutional brands they are associated with.
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  • Bibliometrics, Scientometrics and Informetrics were introduced in twentieth century (later some others). Those years had their values, behaviors and characteristics in the world of higher education. Fraud, misconduct, data fabrication, plagiarism, were not so wide spread as they are now. In recent years we were introduced terms such as gift or ghost in authorship.
  • But we are still using old methods (in new forms) in metric studies E.g. Scientometrics to say who is who in science, or where is where in science... In the age of virtual worlds available to everyone, everywhere, even the meaning of "publish or perish" has changed. Many universities around the globe not only put pressure on their faculty members but also many incentives in different forms, such as cash, to publish more and more... Too many authors have become addicted to see their works published at any costs. They show off their published works, citations, … and "ordinary Scientometrics" with any given names, descriptive or analytic in nature up to now help them. All appear to become "Soft Power" and "Matthew Effect" for those who might not deserve. We have to move to something "Interpretive", "Inferential" or the like to find out or pull back the curtain (please see also my other 2 discussions, related to this one).
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Kindly see also the followingRG link:
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Is this publication real or is it more of an academic scam? The image below is the text of the email sent to me by the publisher please guide me?
Interestingly, this email did not go to the spam folder. This email also has a professional signature; So that it contains postal address, telephone number, website address, etc. I was a little excited at first, but then I started searching on Google. Searching the Persian web, I found two types of news about these publications: I found some news in which it was proudly announced that Master So-and-so's book had been published in English by Lambert International Publications in Germany. Another piece of news was a message of congratulations and gratitude on a large banner on one of the city billboards. Meanwhile, two or three people wrote articles against Lambert Publications, calling them a form of academic fraud and warning others in their blogs and posts not to fall into the trap of these publications.
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I think 'Lambert Academic Publishing (LAP)' is one of the vanity publishers. Do not fall into the trap. I mean do not publish your thesis or book via this publisher, it may bring trouble in your future scientific career.
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My research topic is " Detecting Motor Insurance Fraud Claims Using Machine Learning". I need to get more literature review and how the researches have been done.
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It's really an interesting topic. Best wishes for you.
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The passive role of Banks in handling the banking Frauds and lack of penal mechanism against merchants, who accept and encourage such fraudalent transactions, is a serious fetter for safe payment ecosystem. What is the solution?
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Good point. Customers also need to act with due caution.
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We all know that it is considered academic fraud to publish faked results. What is the punishment for this?
Where to report author or publication?
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write to the author and inform about the same.After then you can decide on based on author's reply.
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On three accounts, the rapid growth in cryptocurrency is comparable to a ponzi scheme. People invest into these because they expect good returns. There is no identified source of generating revenue on the investment. A Ponzi scheme is an investment fraud that pays existing investors with funds collected from new investors. The Ponzi scheme organizers often promise to invest your money and generate high returns with little or no risk. ... Instead, they use it to pay those who invested earlier and may keep some for themselves.
Cryptocurrencies are essentially digital currencies that are not issued by any central authority and depend on the users of the currency for their validation. The validation is recorded on the Blockchain which is there for everyone to see. Since the currency is decentralized, there is no geopolitics involved. Since the transactions are publicly available, implementing counterfeit transactions is extremely difficult. Since the entire system is encrypted using cryptographic protocols, the transactions are secure. Most importantly, they are easily convertible into USD at the moment. Most “serious” cryptocurrencies, like Bitcoin, are limited in number protecting against inflation. Cryptocurrencies have been the darling of fin-tech observers since 2013 and we are presently in the midst of a cryptocurrency bubble with prices of every kind of cryptocurrency shooting through the roof.
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The extreme ups and downs of the value of this currency and the non-backup by governments make the dealings with this currency very dangerous. In addition, money laundering and terrorism, among others, find safe heaven for such currency dealings.
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I am trying to figure out whether language can help in avoiding the frauds in online shopping particularly in Pakistan, It has become a common practice in Pakistan that the sellers are doing frauds by not sending the ordered stuff rather they send low quality or used stuff and then block the buyer.I am trying to analyse the language of these sellers that they use in ads. or in communication with the buyer , whether it shows any similarity or any particular pattern. That might help people to understand not to buy from such sellers. My query is that, is my work relevant to forensic linguists in any way? if yes, which method of analysis should i acquire for my research?
Regards
Asma Saif Ullah
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Perhaps, this research domain falls in the field of forensic linguistics.
Registered branded companies usually use good and formal English which the fraudulent groups may not be doing.
I think forensic author analysis will help you. Comparing the authorial styles of the fake companies and the branded companies will be helpful in this regard.
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Which is best for fraud control? Internal audit vs External audit, Pre-audit vs Post-audit, Performance audit vs Financial audit?
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Ethics with self regulation!
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Is there any research on what's often called 'scambaiting,' when content creators make entertainment content, for example on Youtube or Twitch, by stringing scammers along?
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Kristopher J. Brown Excellent, thanks for those suggestions!
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Recently, upon searching on Google, I found out that one of my research paper is published in Journal of Geography and natural disasters in longdom publication; I have never submitted my paper to them. I asked my Professor Dr Abdulmohsin Imqam, and He is also unware of the submission. Still our research is published on there current issue as short communication. I emailed them to remove the article and got no response. Please suggest me any ideas to file this fraud case and put this wrongdoers behind bars?
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That is dreadful. I would follow Ronán's excellent advice.
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Starting my dissertation proposal and I find myself all over the show.. I need advice and mentorship. Anyone willing to read and provide an honest opinion?
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Interesting
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Hello,
I'm searching for dataset with fraudulent transactions from banking activities. I would like to apply some ML algorithms for purposes of my PHD researches.
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The following paper talks about fraudulent transactions in credit cards which resulted in USD 3 billion loss to North American banks and other financial institutions; you may want to check it out:
Deep learning detecting fraud in credit card transactions‏
A Roy, J Sun, R Mahoney, L Alonzi… - 2018 Systems and …, 2018‏ - ieeexplore.ieee.org‏
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Hello, if you can suggest me a research idea in the emirical part of my doctoral thesis, with the FINANCIAL-ACCOUNTING INFORMATION SYSTEM - AN ESSENTIAL SOURCE IN DETECTING AND COMBATING TAX FRAUD. Thank you very much!
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HI. I suggested that you take a field sample of one of the departments concerned with collecting taxes and study the method of collecting those taxes and the system used in them and the extent of its effectiveness in collecting taxes and the methods used by them to prevent tax evasion
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Hello every one, I wanted to know is there any specific source for the papers on specific category. I am looking for the papers related to online credit card frauds in bank transactions, but I get papers in general related to credit card fraud but not specific to the banking. so any one can guide me what I can do to read papers related with online credit card frauds in bank transactions?
I have tried to search for the dataset for the credit card fraud. I have observed that in most of the papers only one of the kaggle dataset has been used. So I want to know from where I can search or find the dataset related with online credit card fraud in bank transactions? It would be great if I can get help on these?
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Dear D. Shah !
Yes, I have found a few papers related to the topic:
Whitrow, C., Hand, D. J., Juszczak, P., Weston, D., & Adams, N. M. (2009). Transaction aggregation as a strategy for credit card fraud detection. Data mining and knowledge discovery, 18(1), 30-55.
Roy, A., Sun, J., Mahoney, R., Alonzi, L., Adams, S., & Beling, P. (2018, April). Deep learning detecting fraud in credit card transactions. In 2018 Systems and Information Engineering Design Symposium (SIEDS) (pp. 129-134). IEEE.
Raj, S. B. E., & Portia, A. A. (2011, March). Analysis on credit card fraud detection methods. In 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET) (pp. 152-156). IEEE.
Ghosh, S., & Reilly, D. L. (1994, January). Credit card fraud detection with a neural-network. In System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on (Vol. 3, pp. 621-630). IEEE.
Quah, J. T., & Sriganesh, M. (2008). Real-time credit card fraud detection using computational intelligence. Expert systems with applications, 35(4), 1721-1732.
Almost all full texts are available in Google Scholar.
I hope it helps!
Best regards,
Tatiana
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I am conducting a study on the effectiveness of AI towards detecting and averting digital payment fraud. What are the popular AI techniques being adopted in mitigating digital fraud and how could it be enhanced for better results.
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Through optimal selection of training and testing data so we avoid over-fitting problems.
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ith the development of Internet technology, online examination has become more Polar because it helps people save a great deal of energy and time. As an effective and efficient method of teaching and learning, online search fraud can be prevented and the integrity of examination results can be guaranteed. A good examination system should be developed based on real study needs. What Features Should an Online Exam System Include?
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Besides it is a forward-looking and interesting question, the moment chosen by Prof. Maged G. Bin-Saad for this valuable question is well chosen. Before answering this question, please look around you and count how many black offices for solving the exams and assignments are there.
From my point of view, e-learning alone will not succeed without traditional learning. Furthermore, I see that e-learning hasn't achieved the desired aims or results for developing countries and traditional learning is better. This is because there are many black offices for solving exam questions!! These offices made online learning a trading stock that resembles the slave-market.
At least, the hybrid learning of both of them is better than the traditional one.
In any way, exams must be inside the educational institutes (like universities) with the physical attendance of the students. Only by this we can diminish cheating.
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One example is where a meta-analysis includes key fraudulent/plagiarized primary studies.
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The authors who retracted a meta analysis soon after learning it included a recently retracted study think it is essential that systematic reviews should be withdrawn if retracted papers are identified
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The recent US presidential election has seen president Donald Trump accused of fraud by Democrats? Do you think the U.S. election was really fair?
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I have no testable arguments to affirm or deny. However, the same United States government under the same basis would put the change of government at risk if this had happened in another country.
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Forensic accountants and auditors are the people who analyse and examine the financial statements and records of the organisation in order to detect fraud and clear any allegations of fraud .
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what are the strategies to perform hypothesis testing in internal control and fraud detection with the use of cognitive learning AI or RPC technology?
Where can we find the publicly available data source without necessary bias on particular company data (which may involve privacy etc)?
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The hypothesis is related to the research questions. This Internal control/ fraud identification problem is related to risk management. A good risk management framework will encompass risk culture and risk controls. For fraud management it is mostly operational risk controls.
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Dear colleagues, please guide me if such emails should be considered ok or these are fiscal frauds ?
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To identify a financial fraud, e.g. money laundry, AI deployment is not new. Given a large dataset, many machine learning techniques can identify patterns to help to identify these rare events.
Is it possible for some crime lords with bottomless resources to deploy an AI to outsmart the Anti-Fraud-AI (in short: AFAI)? In fact, this is quite easy to answer. The simplest solution would be to flood the financial transaction database with fake positives. An Anti-Anti-Fraud AI (in short: AAFAI) would first identify some fraud patterns, which are most likely identified by the AFAI, then do millions of fake transactions with similar patterns. Other solutions may exist as well.
So what should (or would) an AAAFAI do? and of course, an AAAAFAI do? can this continue infinitely?
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This is also true for terrorist activities over the Internet and terrorism financing. AI could very easily be adopted in countering the finance of terrorism. Best,
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Despite of having several law in force across countries, corporate frauds continue to occur. Even IT and ITES have come in a bigger way to support the industries, still frauds occur. Where is the remedy then?
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Yes
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Today, I was searching my paper. I was completely shocked. This paper was based on my Master of Engineering thesis.
Journal Paper - Thermodynamics and Adsorption Behaviour of the Nano Phases in the Bi-Sn System
I am seeing two name in this paper - 1. Trisza Ray 2. Sandigdha Acharya
Both the people have done fraud case with my paper. Original author is me i.e. Tanay Ray and other author is Sibasis Acharya.
DOI: · 10.1166/jctn.2005.116
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I am not happy with this response. I am have a Journal article on one topic. But somebody is claiming.
There should be an investigation about these two person 1. Trisza Ray 2. Sandigdha Acharya
Both the people have done fraud case with my paper. Original author is me i.e. Tanay Ray and other author is Sibasis Acharya.
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Hi all,
I'm using autoencoder to detect anomalies in my dataset
I used normal dataset for training and detect anomalies on fraud+normal dataset
As I observed so far, autoencoder performed the best at an optimal training dataset size, the ROC, PR AUC went low when the size of the training dataset is too big? Is this because of overfitting?
Please refer to the attached photo below
Thanks in advance!
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In my opinion we can you find the autoencoder in RNN architecture, I suggest if you can you use CNN architecture, maybe that can you give the good results without the overfitting.
I hope that be Claire for you. @ Anh Tram Nguyen
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Dear Sir/Madam, A research item has been added to my name. i suspect it is fraud as it is all in russian and several of the authors are non-russians.
Deleted research item The research item mentioned here has been deleted
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Ase, inasmuch as this may be unfortunate, I guess, as a corrective measure, you can write to the editor of the journal to try and rectify the anomaly. Contacting the corresponding author and stating that you wish to be dissociated from being included in the publication could also provide a way out. Hope it is resolved. Good luck.
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Ethereum is an open-source, blockchain-based, decentralized software platform used for its own cryptocurrency, ether. It enables SmartContracts and Distributed Applications (ĐApps) to be built and run without any downtime, fraud, control, or interference from a third party.
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Please check the below documentation for storage solutions in blockchain :
Regards,
Arpit Shukla.
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Medical fraud is not uncommon. But committing fraud during the times of crisis when you could lose your own life to a deadly disease is unprecedented in the history of medicine.
The recent controversy (Two Huge Covid-19 Studies Are Retracted After Scientists Sound Alarms, New York Times, June 4) has once again revealed an ugly aspect of medical profession, and has already put the world’s two “largest democracies” and the two “most revered” medical journals (NEJM and Lancet) to shame.
Why did reputed medical scientists become dishonest at a time when there was a 'more than ever' need to be more truthful and upright?
Were they only driven by their ambitions for more recognition? Or there is some truth in the allegations that “Big Pharma” were the real actors behind the scenes?
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To me, where is the message again "NO CONFLICT OF INTEREST"?. I think the scientists involved should be dealt with while their sponsors should be thoroughly investigated, and if found guilty should be banned or licence revoked. There are many frauds even before the pandemic, part of the reason why the public suffer harms through fabricated study outcome and influenced pharma marketing strategy.
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And confirmed Zwicky 1929 as a genius for discovering the mechanism.
And exposed CERN as risking earth and using fraud to camouflage this fact.
No one in science or Stockholm objects. One calls this a “conspiracy theory,” albeit a true one for once.
Turning 80 this month, I can afford being fearless and benevolent, combined.
Take care.
May 4, 2020
P.S.: Please, tell me if I am an idiot.
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I don't know how we can disprove something without experimental data. The BB concept is "disproving" itself at is basis (singularity, no entropy,....). Alternatives are being "constructed" and by sure new things need to come in order to put a bit "order" at the conceptual level, in my opinion...
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Hi, 
I want to test a process mining method for detecting fraud in business processes. Are there any public data that we can use for conducting this research?
Thank you 
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Do not ever use public data unless you can copyright it to yourself. Otherwise there are legal and academic problems
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I'm looking to create a data set for all known cases of Corporate Fraud (Financial Statement Fraud in particular) for the purposes of training Data and Machine Learning Fraud Detection Models. If there are any official or reliable sources that you know of that list such companies with the time period in which such fraud too place, please do let me know.
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In order to discourage companies from tax evasion, this method should be adopted globally.
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Dear Researchers,
Hope you are all well and safe. I am currently conducting a research study to explore the impact of coronavirus on the tourism sector including fraud risk in this sector. Could you please fill in the survey below? If you could pass the survey link to your friends, family, and colleagues, I’d be very grateful. Many thanks in advance for your help :)
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I wish you every success ahead of you.
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HIQ is the best name for it, composed out of HI and IQ. "HI" means "I am laughing" in the language of hams (radio amateurs) that I acquired 63 years ago. And IQ (for "I quit") stands for where people start non-answering further questions posed to them by psychologists.
But to be serious: The brightest man in the history of science, Fritz Zwicky 1929, proved that there was no Big Bang and no cosmic expansion. But even though he later-on was proven to in this way have first discovered the new fundamental-physics discipline of Cryodynamics, sister of deterministic Thermodynamics, no scientist on earth is currently ready to support his name in the context of cosmology.
This would not matter very much apart from letting the Nobel committee look a bit old, had his result not simultaneously proven true the fact that CERN's famous LHC experiment is betting earth against reason for 12 years in a row. As CERN itself leaves loudly undenied, by the way, since its latest planetary safety report LSAG from early 2008 carries no date. I called this fact CERNGATE but no one appears to get the point.
But fraud is, of course, infinitely more harmless than a collective inability to understand. Right?
Feb. 20, 2020
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I greatly appreciate your kind support from a totally different domain. We must be tolerant towards our fellow human beings but simultaneously vigilant regarding well-meant attempts at collective suicide. This is the human condition: right?
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The last planetary safety report LSAG (for “Large-Hadron-Collider Safety Assessment Group”) of CERN’s stems from early 2008 but carries no date to look recent. This fraud is called CERNGATE in the literature.
Is there no way to alert a single institution or government to the danger thereby accepted by CERN?
CERNGATE can also be called CERNCORONA in spite of its being 50 times more dangerous.
Which institution on earth has the clout to withhold this scandal from the public and from Assange and Greta’s eyes?
Feb. 21, 2020
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I call this "a loud silence" since yesterday. Okay?
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While doing a research on a subject in social sciences; which of the approaches makes it more reasonable to base the research on one theory, based on more than one theory separately, and examine it by integrating more than one theory? What can be advantages and disadvantages of them?
For example when investigating insurance fraud; the fraud behavior can be related with personality theories, social learning theories, ethical theories or social cognitive theories.
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Thank you for your useful suggestions
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I amworking on a project named Financial Frauds and its impact on macroeconomic stability of a country. i get confused in finding the financial frauds data
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Not sure about what a "proxy" means in your title "suggest me a proxy for evaluation of financial frauds..."; if you need a conceptual framework, you can use Cressey's Hypothesis (1953) and its related fraud triangle. If you require data assessing the impact of financial (and other) fraud schemes on the economy, you can refer to the annual report of the Association of Certified Fraud Examiners (ACFE); the link follows:
Hope this helps.
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In his experience, which political systems are more prone to fraud within the public administration as a state activity. Please back up your reasons. All opinions will be well received. Thank you.
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Neither the left or the right wing political party makes it valid for fraud since fraud is more of a personal interest than a public mediocre .As the human nature ethical thinking they know what is right and wrong irrespective of their source of teaching and learning.political parties should not be carrying the burden of their individual mbers who take advantage of their position and authority in the party.Nevertheless in line with the parties rules and regulations the suspected fraudsters should be banned from the party with immediate effect.
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There are currently just over 2,400 billionaires and 15 million millionaires worldwide. Never before has there been more money and financial activity in the history of mankind. Emerging economic powers that provide multipolarity to the global economic axis. Intense and multiple global networks for the exchange of goods, resources and services. A culture of consumption that increasingly encompasses more nations. Do these conditions encourage greater intent and financial fraud actions? I appreciate your opinion on the subject.
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Financial fraud is inherent in human makeup. With all the laws and regulations, this will be a never-ending struggle like sin. We are born with this and humanity has struggled to overcome this ever since.
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I would like to know what are the methods used in your country to detect and study financial fraud activities in public administration management. Thanks for your opinion.
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The common fraud in the public sector are bribery, corruption, and misuse of authority during public procurement. Internal and audit, strict code of conduct, enhanced ethics and some financial fraud detecting software can reduce and protect corruption in public sector.
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Currently working on Fraud detection for Motor Insurance Claims. How many minimum fraud cases should be there in order to get reasonable AI model.
1. if data size is 5000 samples
2. if data size is 0.1 Million
3. if data size is 1 million.
is there any percentage of based on the size of data?
Regards,
Vikas Goel
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Thanks
Adam Wong
. One question, can we apply SMOTE on data if imbalance is 1:100
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I want to know that is there any relationship can be established between fraud in digital finance and profit of the company.
or we can say that impact of fraud on the net profit.
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I agree with notes presented by Adamu Garba zango and Gorkem Gun.
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Dear all
I am studying about ripening of honey which is practiced naturally in beehives. I then encountered a new term "Artificial ripening of honey". I am not getting any information about this on review/research papers and other websites. Kindly help in this regard. What is artificial ripening of honey? Is it a fraud or way of adulteration or standard practice in beekeeping?
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Different honey bees have different jobs. Some of these bees are “forager” bees, which collect nectar from flowering plants. The foragers drink the nectar, and store it in their crop, which is also called the "honey stomach". The crop is used solely for storage, and the bee does not digest the nectar at all. The forager bee then takes the nectar back to the hive, regurgitating the nectar directly into the crop of a “processor” bee at or near the entrance to the hive. While the forager heads back to the flowers for more nectar, the processor bee takes the nectar to the honeycomb, which tends to be near the top of the hive, and regurgitates it into a hexagonal wax cell. But now the nectar needs to ripen. The processor bees add an enzyme called invertase every time they regurgitate their nectar (and it takes many loads of nectar to fill a cell). The nectar consists largely of sucrose (table sugar) and water. The invertase breaks the sucrose down into two simpler sugars: glucose (blood sugar) and fructose (fruit sugar). By definition, honey contains less than 18.6 percent water, but water usually makes up approximately 70 percent of nectar. During the ripening process, the bees “dry out” the nectar. One of the ways they do this is by fanning their wings, which creates airflow around the honeycomb and helps water evaporate from the nectar. Once the nectar has ripened into honey, it contains so little water that no microbes can grow in it. It is called 'natural ripening of honey'.
But some times due to some unfavourable conditions natural ripening is not possible. So, nectar contains water. It leads to deterioration of honey during storage. This situation demands artificial ripening. So, we can define 'artificial ripening' as the removal of moisture by some artificial method which is not done by honey bee itself.
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in the context of voluntary disclosure , how can we discover the personality of fraud manger ? what are the main characteristics of the personality of the fraud manager, how provide false informations
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The question is not succinct. Please rewrite again so that it is understood by all members for comments.
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I am familiar with using autoencoders to detect Fraud in credit card transactions, But my data is a time series one.
Thanks
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Whistle blowing can be a very important tool for dealing with fraud. However, whistle blowing comes with many challenges.
Can internal auditors blow the whistle on fraud?
Can external auditors blow the whistle on fraud aside expressing the opinion on financial statements?
Are there legal restrictions for whistle blowing by auditors?
I would be very grateful if you could contribute to these questions.
Thank you.
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However, these questions are very interesting and I will follow them.
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Hi there! I'm looking for someone who can help me better understand nonprofits and how they file their taxes. It's for an ongoing research. Preferably someone who is nationally known on this topic through research or practice, and someone who knows how nonprofit taxes are filed, common reporting errors, common fraud, etc. Could be more than one person. Thanks!
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Can I nominate someone from Sri Lanka?
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I am tried to figure out the ways to label the click logs from the advertising log data for ad-fraud detection. Label are Fraud, not fraud.
One way which comes to my mind is rule-based meaning i manually analyze few 100 records and accuse them of being fraud if certain conditions met!
Secondly i could use clustering algos, i tried it but couldn't get it right because i have mixed categorical and numeric data (i tried K-means and K-medoids) but data is very sparse and categorical features tends to expand over time while using one-hot encoding).
Any idea to label the data automatically/algorithmically?
Thanks,
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A simple but quite efficient method may be to perform a semi-supervised learning, for labeling your data and also developing a fraud detection model in this context.
The process is to:
1) manually label a subset of your data as fraud/not or 1 & 0 respectively,
2) train your desired model with the label data - supervised learning.
3) Divide the remaining data set into two (one for re-training and the other for test)
4) test the trained model on the data for re-training and get the corresponding labels.
5) add the newly labeled data to the manually labeled data.
6) Retrain your model on the new data obtain in step (5).
7) Re-test your model on the test data.
This should produced a viable solution.
Note: the entire model development phase is executed at your discretion and expertise
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I am getting unusual requests to accept " a peer review" from "journals" I never interacted with previously.
Could such emails be actually a fraud or phishing email?
How to identify a legitimate peer review request?
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Peer review invitations are very rarely, if at all, fake/predatory, (as opposed to invitations for being a keynote speaker or submission. Being on the editorial team for a couple of journals (BMC Public Health and Journal of public Health Management and Practice), I know journals get a fairly high rates of rejections to peer-review requests. Researchers are genuinely busy, some too busy for an uncompensated service such as peer review. Therefore journals are constantly trying to expand their peer-reviewers' pool.
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Some people believe that the Islamic banks' contracts practice injustice by doing the following:
- weaken trust, solidarity and compassion among people
- Increase fraud and jealousy.
- Increases distrust in markets.
- Increase the methods of fraud and deception.
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Rawan Almesned Thank you very much
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Companies receive daily account statements from their many bank accounts.
The debit / credit transactions that appear on each statement reflect their economic activity and
include information such as the payment / collection method (check,
transfer, ...), the "counterparty" (the payee or originator: suppliers, employees,
customers, ...). These data are conventionally used for accounting or
"Reconciliation" (identification) with prediction. However, for my understanding, those data represent a deposit of
data that can be used for analytical purposes, including:
-For the purposes of combating fraud: to identify atypical payments (by raising, frequency), receipts from unauthorized companies or individuals, ...
-For compliance purposes, to identify unauthorized expense natures based on words predefined key.
-For the purpose of identifying specific transactions; example: search for transactions that represent maturities of the same loan, and which are therefore similar to the exception possibly the date and the amount (but with the same reference, description, ...).
My concern is: How to do it? what kind for algorithm can be better to apply? I think about classification with clustering or random forest but I don't know if it can work. At the end, the system must be capable according to data of companies and bank, say that there is error somewhere( if there is really a error) and this must be accessible with companies and bank . It also difficult to get articles, paper about it.
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Dear Anwar
The data are bank transactions the company will given to me when I start my Intership. But my concern is : Is it possible to build a bank reconciliation system fully based in machine learning and how to proceed?
regards
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Hi everyone, i conducted a questionnaire of 22 likert scale questions to measure the impact of accounting ethics on accounting fraud, after collecting the data i got the mean for each set of questions that represent an independent variable. my question is now how to compute the dependent variable which is accounting fraud through the answers of the 22 questions using spss ?
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You go to Transform in SPSS and click on Compute variable. Give it a new name in the target variable box. Click Type and label and click on label box and write total fraud scores. Click continue. Then from your list of 22 items you click the first item. Click numeric expression and move into the box. Click on + on the calculator. Repeat until all 22 items are there. It looks like fraud1+fraud2+fraud3.....fraud22
Check and correct if needed. Click OK and Run. This is your dependent variable, which are your independents?
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Is it possible to help me with similar sources or research for the purpose of completing my research projects on the development of electronic payment control systems to reduce fraud and fraud?
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Dear Adheem Naeem,
I suggest you to see links and attached files on topic.
the changing nature of us card payment fraud - The Workshop on the ...
REDUCING FRAUD IN ELECTRONIC PAYMENT SYSTEMS The 7 ...
Electronic Payment Fraud Detection Techniques - ResearchGate
Fraud risk in electronic payment transactions | Journal of Money ...
Risk management for electronic banking and electronic money ...
mitigating Payments Fraud risk - JP Morgan
Electronic Payment Systems - Eindhoven University of Technology
Best regards
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Hi,
Does anyone know a questionnaire that examines a person's risk of falling victim to fraud?
Thanks
Ya'akov
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Thanks.
If someone knows other questionnaires I would appreciate if you can provide details.
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Forensic accounting is used for fraud examination and fraud examination, and to understand the depth and width of the financial scams happening in any economy. The objective of initiating this discussion is to understand the significance of forensic accounting in Corporate Finance.
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Forensic Accounting is very modern and important information base of checking of legality operational and financial performance of enterprises.
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Recently I discovered that my colleagues from the laboratory I was working in, published three different papers without my name as an author. I performed the experiment, take care of the animals, was working on the whole thing (analysis included) for months as well as anyone else. I even got the money to renovate the lab, but got fired from the head if lab. I was too busy solving my existential problems to notice that, and finally left the country. What would you do?
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As a famous scientist Nikola Tesla had commented on issues of the sort that he experienced (two quotes are particularly suitable: "I don't care that they stole my idea . . I care that they don't have any of their own" and "The present is theirs; the future, for which I really worked, is mine."). So, to any researcher who has done something valuable you will encounter many more such misfortunate situations and characters with rather poor academic ethics (as thief is a thief either way you take it and, strangely enough, the more productive/creative the more this aspects amplify). So, focus on what matters and that is progress of your work - inadequately behaved intellectuals should not bother you, your well being and your plans for moving forward. Good Luck and let me close it with Victor Hugo's saying "You have enemies? Why, it is the story of every man who has done a great deed or created a new idea. It is the cloud which thunders around everything that shines. Fame must have enemies, as light must have gnats. Do no bother yourself about it; disdain. Keep your mind serene as you keep your life clear."!
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Hello Everyone
I am wondering if using group discussion to support statistical results of quantitative research method can be an adequate technique in sensitive topics such as fraud, corruption, etc. ?
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In mixed methods research, what are known as "sequential explanatory designs" use qualitative methods to follow up on the results from earlier quantitative studies (QUANT --> qual). The basic purposes for these designs is to get more insight into how and why the quantitative study produced the results that it did, which often includes getting illustrative quotations from the participants.
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What is benchmark of fraud investigation?
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Thanks
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Ask questions on fraud; fraud detection; fraud investigation and fraud prevention.
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Please share your reply in English.
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Recently, I have gone through an article in a prestigious journal where most of the figures representing the main theme is manipulated. Do I need to provide any data from my side to claim the fraud?
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I am agreed with Subir Bandyopadhyay
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Abstract:The part of the higher education sector in the UK in which providers are not publicly-funded (including for-profit, not-for-profit and charitable) has been expanding considerably under Government encouragement. This paper aims to clarify the practical and public policy issues now emerging, by tracing the history of the emergence of this policy in the wider context of trends in higher education policy in the UK, and with reference to the changes brought about by devolving higher education to the 'devolved administrations' of Scotland and Wales. It examines the claims made by alternative provider lobbyists that they will be able to provide something for students which would be different and better. It looks at the mounting evidence, including the findings of the Quality Assurance Agency, the National Audit Office and the Public Accounts Committee, that a number of alternative providers were guilty of bad practice and even fraud in taking advantage of the availability of Student Loan Company funding for their students. The penultimate section describes the attempt by a small group of alternative providers to form an organisation for leaders of the sector and to dissociate themselves from these trends and emerging problems. The article concludes with the implications of the White Paper, Success as a Knowledge Economy, and the Higher Education and Research Bill, both published in May 2016 for the risks and implications of this significant proposed reconstruction of the system of UK higher education.
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Hi,
I also tried to search for the paper you indicated but couldn't find it. I would like to suggest that you send a request email to the author.
Best wishes
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Assume that to get the data of a variable “direct victimization of crime” respondents will be asked below questions with yes/no options. After collecting the data from these items how can this data be assembled to measure a variable direct victimization of crime.
For the sake of question, I am here giving you the examples of questions which would be asked to measure direct victimization of crime, and options for answers are yes/no
Within the past year, were you or any family member a victim of the Stolen goods/belongings from car?
Within the past year, were you or any family member a victim of the vehicle theft?
Within the past year, were you or any family member a victim of the Burglary into house?
Within the past year, were you or any family member a victim of the mugging?
Within the past year, were you or any family member a victim of the fraud?
Within the past year, were you or any family member a victim of the Computer (internet) crimes?
And what if options are given in Likert scale rather than yes/no option.
Thanks and Regards
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Dear Michelle Yes. thanks for your time. Regards
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Hi,
What do you think causes the phenomenon of economic fraud against the elderly? Why are they more likely to be victims of fraud? It would be nice if you could base your opinion by referring me to good articles on the subject.
Thanks,
Ya'akov
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Thanks Enrique and Michael!
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I am interested to gather Grounded Theory definitions of the above four concepts. By Grounded Theory definition, I mean the definition/ description/interpretation of the above concepts (or any of the above concepts) based upon your real experience. That means you will have to explain the context/experience/observation that gives rise to your unique interpretation.
Context is important, (Personal/Professional), while maintaining ethical anonymity of course.
Thank you very much for your participation in the discussion.
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My work, over the past decade and 1/2 has been based on "grounded theory" related to my (new) topic, "Missed, Hidden and Denied" history, in the context of real local conflict both in CA and in Alabama. My original, doctoral work related to the "New Jim Crow" the school-to-jail pipeline, and school discipline. I became a discipline hearing officer and administrator for a rural CA school district. In CA as an educator, I've experienced considerable "deception" because of the "silencing" of important leaders and events - thus a "fraudulent" narrative of regional history. History that speaks to some present conflicts and controversies related to racism, the "cult of the lost cause" and the national politics moving backwards toward the 1850s anti-immigrant sentiments. In terms of real lived experience, I have been under attack personally as an advocate for civil rights and environmental protection as the President of a John Muir group located in a rural part of CA near Yosemite. We've brought a genuine grand jury investigation against a 'right wing" supervisor who pushed through a "non-sanctuary" county resolution and who personally attacked a teacher who I mentored in a local school because his wife is (Mexican-Indio) Latina and a dreamer, with a college degree from a CA State University a very complicated and disturbing story. New grounded theory research in the works. In Alabama, my research relates to the racism exposed during hurricane Katrina as I began working with a teacher mentor I'd had as a young man in the 60's with a Civil Rights experience in the Black Belt Region of Alabama, near Selma. Both grounded theory (related) articles are now published. (1) Chapter 38, pp. 729-749. "Searching for Social Justice: An Examination of the Views of Alternative School Educators in the San Joaquin Valley of CA" (2014), In: Spinger International Handbooks of Education, International Handbook of Educational Leadership and Social (In) Justice (vol 2) Ira Bogotch & Carolyn M. Shields, Editors. (2) Chapter 1, pp. 1-47. "More Than Race: The "Full Employment" Civil Rights Work of Robert Brown, Alabama's First Black School Superintendent" (2018) In: Southern Studies: An Interdisciplinary Journal of the South" New Series: Vol. XXV, No. 1, Spring/Summer 2018, Published by the Southern Studies Institute. I'm a recently retired "teacher" and educator in CA and in coming back home to CA after 30+ years in the South was surprised to learn how the racism and anti-Jewish, KKK related movements I'd witnessed and experienced in the South during the Civil Rights era, had spread across America to the very place I finished my education and teaching career after completion of a PhD at the University of New Orleans.
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A t the moment I'm developing ML based model for the prediction frauds. But, I have a small issue on feature selection for the my proposed model (Fraud Prediction).I have gone through Several articles and tools to get the best features that describes the model more accurately. 
  • Weka > Select attribute 
  • Scikitlearn  > sklearn.feature_selection
  • Scikitlearn > forest.feature_importances_
Unfortunately non of packages offers bench mark or rule of thumb to select best features that describe the model. I would be appreciate that if you could kindly let me know the best mechanise/method to identify best feature which I could use for the prediction model.
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For fraud detection, you will need more than maths to identify your best predictors (features, independent variables). You will also need to imbed yourself in the problem domain, and then use your head. Think carefully ... which of your statistically predictive features can't be easily changed by the perpetrator? I ask you this because, as soon as you put the resulting model into production, blocking the perpetrator's fraud attempts, the perp will get instant feedback from your intervention and try to modify his or her own behavior to avoid your trap. If your silver bullet variables represent behaviors that are easy for the perp to change, your model won't remain predictive and you will soon have to start all over again, cat and mouse. Try to choose a combination of predictors (non-linear combo style) that are too subtle to be easily modified by your adversary. The goal is to keep the perp engaged in the same stupid behavioral patterns as long as possible so as to make your fraud hunting more like fish farming than ocean searching.
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I received a cd3 T cell isolation kit from a Miltenyi distributor with 1 month left on its shelf life. I called them but they said all Miltenyi kits have a shelf life of 6 month. Is this true or a case of fraud?
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I have used Miltenyi kits after 5 years from the expiration date and they work perfectly. Antibodies can last forever.
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How is it that despite the global economic crisis as a consequence to the practice of neo-liberal policy prescriptions, despite the turn-around in the globalization of the free markets with new protectionist policies being promoted by the United States, Europe, China and India, the discipline of Economics as it is taught in class rooms, continues to be dominated by Neo-Classical Micro-Economics, Monetarist & New Classical Macro-Economics and the free-radical Financial economics? Is it not high time that we promoted heterodox approaches in economics and thought a fresh on more appropriate and relevant analytical frameworks in the contemporary context instead of harping on neo-liberal ideology substituting for knowledge?
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Thank you very much Prof.Christopher Nock for that reply. I very much appreciate the way you seem to suggest a process of change in ideas with a lag. That is very optimistic. Yes, there is bound to be a lag in learning as well as coming up with alternative thinking in place of an established set of ideas holding dominance.
It's however, a decade now after the world has been hit by the global economic down turn. The world economy is still struggling hard to recover from it. Its been nearly the same time since the French Commission Report engaged in a self critical assessment as to whether the analytical framework economics as a discipline has taken vis-à-vis development and the policy approach it has encouraged have misrepresented development, because of which economists failed to see the crisis coming?
Given this long duration, that new ways of understanding have not yet seen the light in our class rooms, in terms of reshaping the curriculum, altering the weight assigned to the so called 'main-stream' thinking (occupying nearly the major part of compulsory courses), should we be wondering why there is so much of resistance to learning especially in institutions of higher learning?
Institutions of knowledge are supposed to be path-finders in moments of crisis. On the contrary if they themselves end up being slow learners, one would have to explain the underlying reasons for it. Compare the current experience with the one which involved the demolition of Keynesianism. Do we see some distinct difference in the role of the academia, academic institutions and organizations of today?
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I am working on the effects of bank related fraud on the net worth of banks in different country with a few to compare the seriousness of regulators in combating the scourge.
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It is difficult to get reliable data on bank fraud particularly related to developing and under developed countries.
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I know that the issue is hard. Let us try to be very careful not to offend other people, try not to mention the names as much as it will be possible; certainly avoid people who are around on RG; and let us discuss just the methods. So let us discuss the problem apart from the RG and just in principle. Let us try to examine when political propaganda intervenes in science and what are their methods.
Therefore the essential point is the discrepancy between facts and the interpretation of the facts in science under influence of politics, or :
What are the methods of political propaganda in science, scientific media and scientific communication? How to protect science from politics?
This may concern opposing some scientific concept by using political action or inverse: the opposing some political orientation by using fallacious scientific methods. Using science is very effective to persuade the masses and can be easily dissimulated. The important aspect of the propaganda method is to imply the conclusions and to avoid establishing links with the discussed facts.
As far as I know, we had on RG at least 2 such threads: during the last elections in the US (trying to discredit Donald Trump), and one recent and still running - on plagiarism (trying to damage certain Serbian politicians). There are certainly some others of which I am not aware.
The common feature of such attempts is to focus the discussion on some personality and to avoid clarification of the facts and insist on some more general aspects, structural or contextual aspects, persuasions or general principle without establishing the links with the discussed facts. Number of logical fallacies are used and none of them is specific for those discussions.
May be we should concentrate on relation of the political propaganda and science, morality of publishing, and scientific and political paradigms vs. empirical facts.
Or, the essential point is that since politics is often blind for the facts, the question is how deep politics reaches into science?
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Interesting questions.
1. I don't think science can be completely free from the politics because science and politics are generally inseparable. For example, political science.
2. Scientists also live in the human society. Hence, they are also influenced by political opinions from the outside. The verb "infiltrate" conveys the problem. Without an independent opinion in the society, it is very hard to hold own opinion.
3. To influence scientists, politics can define studies and pay for purposes that are predefined by political wishes. For example, there are movies about Nazi-time, where some scientists say, they are scientists and are not interested in politics at the beginning of the movie but later they are confronted with politics and have to make their decisions that conform to the ideas they rejected before.
4. To explore methods of influence by politics, I would study historical books that explore a particular sinister time or contact historians -- maybe, they already have findings on the issues you are interested in.
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Recently, many of capital market authorities (e.g. New York Stock Exchange; Malaysian Securities Commission) require listed companies to establish internal audit function, as result of preceding corporate fraud (e.g. Enron). In practices, this function is performed either by company's employees or by external provider (other than the company's external auditor). Therefore, I will be grateful if you can state whether listed companies in your country (or other countries based in your knowledge) are required to have entirely in-house IAF or optional (entirely in-house, entirely out-sourced or co-sourced). Thank you.
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Thank you dear Peter for sharing your country practice.
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