normalize with respect to that Now on the table I did take one step toward uh away from the raw frequencies by putting uh percentages So that the percentage of time of the of the times that a person spoke what percentage eh w so Of the times a person spoke and furthermore was involved in a two overlap what percentage of the time were they the overlapper and what percent of the time were they th the overlappee And there it looks like you see some differences um that some people tend to be overlapped with more often than overlapped but of course uh i e this is just one meeting uh no statistical testing involved and that would be required for a for a finding of any kind S so scientific would be reliability statistically incorrect to conclude from this that Adam talked too much No something no No actually no that Yeah no actually statistically correct but Yeah Yeah yeah right Yeah right And Excuse you know I don't see a point of singling people out now this is a case B where I obviously I rather the enjoyed numbers it speak Yeah but yeah themselves Yes Well right so you you know don't like nee OK not not saying on the tape who did better or worse because Sure don't think that I you know and and th a case where of course human subjects people would say be sure that you anonymize the results and when Yeah so this might what do this This is actually when Jane sent this email first is what caused me to start thinking about anonymizing the data Well fair enough Fair enough And actually Yeah point is not about an individual the point about tendencies toward you know different styles different speaker styles sure And it would be you know of course also the question of what type of overlap was this and w what were they and i and I and I know that I can distinguish at least three types and probably more I mean the general cultural idea which w uh the conversation analysts originally started with in the seventies was that we have this strict model where politeness involves that you let the person finish th before you start talking and and you know I mean w we know that an and loosened up on that too s in the intervening time that that viewed as being a thing I mean that you have the style from the East Coast where people will overlap often as an indication of interest in what the other person is saying And Yeah exactly Well Yeah you go Fine alright OK And and you know in contrast so Deborah d and also Deborah thesis she talked about differences of these types that just different styles and um you you can't impose a model of there of the ideal being no overlaps and you know conversational analysts also agree with that so now universally a ag agreed with And and als I mean I can't say universally but anyway the people who used to say it was strict um now uh don't I mean they they also you know uh uh ack acknowledge the influence of sub of subcultural norms and norms and things So um Then it beco though so just just superficially to give um a couple ideas of the types of overlaps involved I have at the bottom several that I noticed So uh there are backchannels like what Adam just did now and um um anticipating the end of a question and simply answering it earlier and there are several of those in this in these data where because people talked to each other um we know basically what the topic is what the possibilities are and w and spoken with each other so we know basically what the other style is likely to be and so and t there are a number of places where someone just answered early No problem And places also which I thought were interesting where two or more people gave exactly th the same answer in unison different words of course but you know the basically you know saying yes or you know or ev even more sp specific than that So uh the point is that um not necessarily a bad thing and that it would be im i useful to subdivide these further and see if there are individual differences in styles with respect to the types involved And all I wanted to say on that unless people have questions Well of course th the biggest um result here which is one talked about many times and isn't new to us but which I think would be interesting to show someone who isn't familiar with this is just the sheer number of overlaps Yep Yes Oh That OK that Yeah Right that that um a relatively short meeting a forty forty plus minute meeting and not Hundred only were there two hundred and fifteen overlaps but uh I think one one minute there where there where where there wasn't any overlap I mean uh throughout this thing Well at the bottom S be have the Yeah interesting three So are four have four minutes all together with none none Oh But so it the w three did have s stuff going on Yes was speech Yeah But just no overlaps OK so if the be this interesting to see what the total amount of time is in the overlaps versus Yes exactly about Yeah ask yeah Yeah Yeah pro have project that comes infor I Hmm th that information now Oh about how much The is the it duration of eh of each of the overlaps O oh the the average length M I I haven't averaged it now but uh I I will uh I You will don't do know the the study of the with the with the program with the uh the different uh the nnn distribution of the duration of the overlaps OK you you don you don't have a feeling for roughly how much it is mmm Yeah Because the the uh is The duration Yeah is uh the variation the variation of the duration is uh very big I on suspect that it will also differ but depending on the type of overlap involved Yeah So backchannels sure Because brief on and your surface eh a bit of zone of overlapping with the duration eh overlapped Yeah and another very very short Yeah Uh i probably very difficult to to because the the overlap is uh on is only the in the final S of the of the the fin the the end the end word of the um previous speaker with the the next word of the the new speaker Um I considered an overlap but very short an X with a and the idea is probably eh when eh when eh we studied th th that zone eh eh we h we have eh eh confusion with eh eh noise With eh that Yeah fricative sounds but uh Yeah have