The history of science knows many falsifications. The journal Nature estimates that about a third of researchers are involved in plagiarism and data falsification. Of the 7,000 scientists surveyed by the journal, 33 percent admitted to violating scientific ethics. When it turns out that falsified data were used in the studies, errors or plagiarism occur, the journal announces the retraction of the article and publishes a retraction. Investigations are often initiated by colleagues who carry out similar scientific activities and closely follow the news in their field. Let's start with some statistics. Between 0.02% and 0.04% of scientific articles are retracted after publication. Often the falsification of the results is due to the fact that scientists turn a blind eye to the imperfection of the research methodology and ignore the requirements for experiments with people.
For example, subjects, when it comes to psychological research, should not receive clear instructions on how to act in a given situation, scientists should not interfere. This is where Philip Zimbardo, the author of one of the most famous psychological experiments of the 20th century, the Stanford Prison Experiment, stumbled. He argued that people in power will dominate and treat their subordinates cruelly, even if it is not required. Zimbardo claimed that he and his team did not give any instructions to the subjects. An article by American writer and researcher Ben Blum reports that this is a lie. He found in the archives of Stanford University a recording of a conversation between Zimbardo's assistants and one of the "jailers": they explain to him how to behave with the "prisoners". In addition, Bloom spoke with several participants in the experiment, and they admitted that they feigned cruelty, as well as psychosis and depression.
But, if until 2000 the reasons for recall were mainly falsified data, then in the 21st century this is mainly due to plagiarism. Plagiarism is a very serious crime in science. After all, this is the deliberate appropriation of the results of research, works of literature or art. In simple terms, plagiarism is theft, which entails criminal or administrative liability. If the theft of property is easy enough to prove and bring under the responsibility that comes in the Criminal Code, then the theft of intellectual property is much more difficult to prove.
Modern scientists should publish. They simply have no other choice - articles are needed in order to talk about discoveries, get a grant or degree, confirm the title, etc. Even the famous indicator of scientific productivity - the Hirsch index - is calculated based on the number of publications. But not all scientific journals are equally useful. Therefore, high demand has led to the emergence of thousands of publications with a dubious reputation. They cannot offer high-quality reviewing and editing, but they are ready to publish an article for a fee. Such journals are called "predators" and conscientious scientists try to avoid them. But it is not easy to calculate predators, because they skillfully disguise themselves.
Therefore, the identification of fakes - the need to protect public consciousness from false goals - involves, first of all, checking information for fake content. Lots of people are doing background checks these days. Just like journalists, scientists have to check information regularly before using it in their work.
Why you need fact-checking:
In journalism, fact-checking is aimed at protecting copyright publications from newspaper gossip, artificial elevation of “degree” or disinformation. In the scientific community, fact-checking is directed in a slightly different direction:
to eliminate near-scientific information presented as reliable facts;
to check the results of a study in a crisis of reproducibility - this, unfortunately, is a fairly common phenomenon when articles with unverified research results are published;
against the use of distorted data (factoids);
against the manipulation of facts, that is, the deliberate arrangement of facts in such a way as to lead the reader to a conclusion favorable to the author;
against the manipulation of public opinion, that is, the desire to embellish the facts, distort them in such a way as to push readers to the desired decision.
The development of content analysis technologies, research in the field of data analysis creates great opportunities for researchers in this field. Therefore, Exorde as a knowledge network can use the unstructured content of the Internet and perform a first-of-its-kind analysis of the virality of information circulating throughout the network.
Exorde is run by its DAO (Decentralized Autonomous Organization) and uses community votes and polls. Management will be decentralized among all members of the community. Collectively, they will be able to change the internal rules and parameters of the systems (rewards, limits, delays, scheduling, etc.) and will have a built-in reputation system. These mechanisms are designed to continually align the interests of the community and its governance for the benefit of Exorde.
The Exorde Labs team also announced the launch of Testnet v1.1. After all the improvements, data processing, observations and protocol setup of Exorde, anyone can become a tester.
The team has now released web scraping modules (only compatible with Windows for now. Linux and Mac coming later this summer) to participate in Testnet. At the moment, scraping (targeting an automated data collection process) is carried out on Twitter and Reddit. As we move forward, resources will expand, in which data collection will also take place. Moderation and formatting processes are also available. Moderation is a deterministic validation process that checks whether the URLs provided during scraping are valid (relevant, not dangerous, real data, etc.). Formatting is the process by which each block of data is broken down into sentences and parsed separately to link the information at a more detailed level.
At the next stage, it will be possible to download modules with open source code and take part in the next stage of the testnet. This phase will include more detailed web panels showing blocks of data being mined on the Exorde network, the number of free and employed workers, protocol details with additional statistics, URLs, and more. And at the last final stage, Testnet v0.2 will already be with improved staking mechanisms, rewards and dynamic protocol settings.
Written by Bimevox
Join to Discord: https://discord.gg/e4y7bjQSwW
Twitter: https://twitter.com/ExordeLabs
https://exorde.network/
Reddit: https://reddit.com/r/Exorde
@ExordeLabs #crypto #web3 #protocol #exorde $EXD
