Lets say we decide on 1000 datapoints as a nice round number to start with. As you increase the number of people in the system the number of connections increases as illustrated below.įormulae for calculating triangle numbers So we also need to look at the relationship between the number of kink profiles and the number of potential kink negotiations we can generate a KCI for. We would also have a fair amount of selection bias if the data was collected from people who choose to fill this out for personal use – people who spend their free time using kink negotiation tools are probably going to have more kinks than the general population and that’s potentially going to affect the distribution of KCIs.Ĭrucially the data we are looking for to formulate our probability distribution is not the people filling out the kink profiles, but the KCIs we can generate by comparing any two kink profiles. So how much data would we need to make this work? With statistics it’s kind of the case that more is better – the law of large numbers dictates that the larger your sample size is the more closely your results should reflect the parameters of the whole population. Illustrative normal distribution graphs – produced using this But if it increases by the same amount again to 0.6 your percentile ranking only increases by 15% this time, to 84%. Increase that to 0.55 and your percentile ranking rises 19% to 69%. A value of 0.5 would put you above 50% of matches. For example, lets assume that the average KCI is 0.5, with a standard distribution of 0.1. As you get further from the centre of the distribution the data gets a lot more spread out. I’m not going to go too much into the normal distribution here because it gets complicated – but here’s a good video if you do want to know more.Įffect of skewness on distribution, image pinched from WikipediaĪn important thing to note is that the closer you are to the average value (the middle of the normal distribution) the more a change in the KCI effects your percentile ranking. It’s possible it could be a skewed dataset (as shown in the picture below), but that still doesn’t change things too much. I’m going to assume it follows the normal distribution because (as the name suggests) that’s what normally happens. But to do that we need data.įirst off lets talk about how this data could be distributed. this is higher than 80% of KCIs, that would give some context of how closely matched the two kink profiles are. But what if you calculate that you and your partner have a kink compatibility of 0.6? Is that high, low, amazing, disappointing? I don’t know, nobody can really know at this point because we don’t know what the typical range of scores are.Ī more useful measurement tool might be percentile rankings, e.g. We know the mathematical limit of the kink compatibility index (KCI), it is impossible for it to return values below 0 or above 1. A list means we’re less likely to miss out something important in our kink negotiation while excited by the potential to play together. Also, I’m extremely prone to getting distracted. Going through different kinks and comparing answers with a partner works for me. As part of this you also start to understand what makes each other tick. For me that’s what a kink negotiation is all about, not simply comparing kinks but using it to open up conversations about what you have in common and start bouncing ideas back and forth. The way I’ve found it useful was as a starting point for conversations. If you’re new to this and unsure then there are some useful resources out there, but ultimately it’s about whatever helps this conversation with your partner or partners. How exactly you go about a kink negotiation is personal. It’s a tool to aid a discussion of shared kinks and build a connection grounded in Risk Aware Consensual Kink. So the honest answer is that you should use it however you want.
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