Okay, man. I don't expect you to do anything else at this point. I will continue researching this, and WILL report the Kryptogames site if I can find additional advocacy sites outside of Steemit to do so. This is part of my larger research effort into blockchain gaming. I also have 2,746,630 Krypto Gamers Tokens, and 330 Good Gamer's Token which I will hold and then sell at a time when their value is enough to partially/fully offset the 5,000 Steem loss I have experienced, and then buy that Steem back. Actually, at the current $0.17 that is ~ $850 USD, and I see that my Kryptogamers token holding has been up to as much as ~ $100 a few times in the past month. So hopefully it will be possible to recup some/most of the loss and then never gamble on these sites again. At least with the potential to earn the tokens there is a CHANCE of recuperating something, REGARDLESS of what the Kryptogames admin does. Once those tokens are in Steem-Engine they are OURS to hold or sell as we see fit. So that is at least ONE plus to all of this. Good luck.
RE: Delving into Fairness: Kryptogamers.com
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Delving into Fairness: Kryptogamers.com
These sites will all be exposed in due course. Best to stay away from them all. I have been looking at the site you mentioned it looks good but not sure how legit it is. Alot of these types of sites here in UK will approve anything and give out awards for a price and these are 'legislated' so what hope is there in crypto land lol. Do keep me in the loop see how you get on and will be playing just to take some Screenshot if required at a later date
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Fairness is a concept that has been central to discussions of ethics and justice for centuries. At its core, fairness involves treating people equally and impartially, without discrimination or bias. It is a fundamental principle of many legal and moral systems and is seen as a key component of a just and equitable society. Must visit receipt printer to get the info about printers. In recent years, there has been growing interest in delving into fairness in a more systematic and scientific way, particularly in the field of machine learning and artificial intelligence. As machine learning algorithms become more prevalent in our lives, there is a growing concern about the potential for bias and discrimination in the algorithms themselves.
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