Simple scaling of hedonistic values can become fairly imprecise when given scales, especially when comparing elevations of euphoria or emptiness. Hedonistic Values may be more precise and specific than other methods of description. If there is more variation in describing experiences, it can fill gaps in tacit knowledge that fails to be articulated into its comprehensible constituent, if any at all. Firstly, the person of experience should list every emotion they experience in x situation. Such that we converge the plethora of words into an underlying topic. This can be done by scaling different temperaments in relation to each other on a scale, which then chooses the most ideal “feeling” closest to all the emotions the user had mentioned.
For example if we have the word distraught and annoyed we may converge them to the word “temperamental”. This may be done heuristically, but to avoid major biases, it’s best to plot the vast variation of hedonistic traits on a graph (Which is time consuming, at the expense of precision).
Lastly, each trait in itself that was in result of the users experiences would be scaled out of 10 or 20, but this value can be endlessly adjusted towards the overall hedonistic framework of the individual which is far more accurate. Note you may utilize a value for each semantic that comprises an experience, but to get obtain the isotope/value of the output trait, you take the semantic list the user mentioned and obtain its mean (Sum of each scale value / Total amount of words(description) ).
Hedonistic Isotopes:
Abstract
Simple scaling of hedonistic values can become fairly imprecise when given scales, especially when comparing elevations of euphoria or emptiness. Hedonistic Values may be more precise and specific than other methods of description. If there is more variation in describing experiences, it can fill gaps in tacit knowledge that fails to be articulated into its comprehensible constituent, if any at all. Firstly, the person of experience should list every emotion they experience in x situation. Such that we converge the plethora of words into an underlying topic. This can be done by scaling different temperaments in relation to each other on a scale, which then chooses the most ideal “feeling” closest to all the emotions the user had mentioned.
For example if we have the word distraught and annoyed we may converge them to the word “temperamental”. This may be done heuristically, but to avoid major biases, it’s best to plot the vast variation of hedonistic traits on a graph (Which is time consuming, at the expense of precision).
Lastly, each trait in itself that was in result of the users experiences would be scaled out of 10 or 20, but this value can be endlessly adjusted towards the overall hedonistic framework of the individual which is far more accurate. Note you may utilize a value for each semantic that comprises an experience, but to get obtain the isotope/value of the output trait, you take the semantic list the user mentioned and obtain its mean (Sum of each scale value / Total amount of words(description) ).