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<p>thanks for the article</p>
<p>I'm (?not?) surprised to learn (from this article and followups
to it) about hyperscanning and the mature(ing) study of "<strong
data-start="2624" data-end="2669">\u201cmulti-brain\u201d neuroscience</strong>,
which treats social interaction as a <strong data-start="2708"
data-end="2739">co-regulated dynamic system" </strong><span
data-start="2708" data-end="2739"> but it is fascinating to
discover that this is as quantitative as it has become and that
folks are trying to effectively study collective/symbiotic
cognition/intelligence/consciousness.</span></p>
<div class="moz-cite-prefix">On 10/23/25 7:15 am, glen wrote:<br>
</div>
<blockquote type="cite"
cite="mid:b9f75694-ef0d-40d7-b2eb-9e1631b77db3@gmail.com">ERP-based
interbrain causal model reveals closed-loop information
interaction in interpersonal negotiations
<br>
<a class="moz-txt-link-freetext" href="https://www.sciencedirect.com/science/article/pii/S1053811925005440">https://www.sciencedirect.com/science/article/pii/S1053811925005440</a>
<br>
<br>
"This causal model provides a mechanistic explanation of how
proposer-responder pairs perceive and adapt to each other\u2019s
decisions, facilitating shared attention and behavioral
coordination in reciprocal, asymmetric negotiations."
<br>
<br>
On 10/10/25 11:55 AM, glen wrote:
<br>
<blockquote type="cite">Well, as a fan of ChatGPT, I'm sure you've
submitted this article to it and have a ChatGPT-shaped extruded
opinion of it. >8^D I may have a similar one, having gotten
analyses from Gemini and Claude. My initial worry was later
identified by Claude, but not Gemini: no diversity analysis of
the 384 undergrads ... not even male vs female numbers? Maybe I
missed it, though I did look at the 2 Supp docs. I stopped short
of researching estimates of diversity at Beijing Normal. Pffft.
Both Gemini and Claude said their methods were high quality. Is
it high quality to *not* report such things? No.
<br>
<br>
Anyway, the analogy of their bipartite game with small scale
organizations like teams and leagues is pretty good, I guess.
Though not at all perfect. I'd argue that something like
Dunning-Kruger would apply. We had a forward on our soccer team
who seriously thought he was better at *everything* than every
other player on the field. And, to be fair, he was better at
everything *except* fairness. When he was allowed to dominate,
we won. When he wasn't allowed (or wasn't playing), we did about
average.
<br>
<br>
But we all hated that m0th3rfvck3r, and his @ssh0l3 dad. But we
won ... a LOT. So ... for a team of middle schoolers who weren't
financially invested in the outcome of such games (yet we
suffered privately at home when we lost a game, including both
psychological and physical abuse) ... You tell me, what does
"fair" mean?
<br>
<br>
On 10/10/25 8:21 AM, Steve Smith wrote:
<br>
<blockquote type="cite">Listening to Trevor Noah in an extended
interview (1:26:00) with Bernie Sanders "Who Owns America?" I
was browsing my "to read" queue(s) and tripped over the
following paper of relevance to a point Trevor was making
about the inherent fairness in sports.
<br>
<br>
Trevor and Bernie exchanged examples of how Shaq's physical
prowess lead to new rules which handicapped his most acute
capabilities and how Golf (of all socially irresponsible
sports) uses the (literally named such) handicap system to
allow individuals of widely different levels to (potentially)
play together.
<br>
<br>
I'm generally NOT a fan of either (organized-competitive)
sports nor politics as they are practiced because despite all
the aspirations and claims in both domains (what is Democracy
if not an aspiration to fairness?) the dominant theme seems to
be "how can I game the game?". Which suggests that
game-theory is the meta-level at which the dynamics can be
studied (and adjusted?) to match our aspirations?
<br>
<br>
More objective (and smarter) people here might be able to suss
out more specific implications of this paper on the
Socio-Economic-Political domain than I am here...
<br>
<br>
<br>
*Coordination of network heterogeneity and individual
preferences promotes collective fairness*
<br>
<br>
<a class="moz-txt-link-freetext" href="https://www.cell.com/patterns/fulltext/S2666-3899(25)00141-2">https://www.cell.com/patterns/fulltext/S2666-3899(25)00141-2</a>
<br>
<br>
<br>
Summary
<br>
<br>
There are intensive debates about whether heterogeneous
networks promote prosocial behaviors such as fairness and
cooperation. Theoretical models predict that network
heterogeneity plays a positive role, but this prediction has
not been validated by experiments. We reconcile this debate by
conducting experiments with two-stage ultimatum games on
networks. In the first stage, we identify responders with
strong fairness preferences, referred to as leaders. In the
second stage, when leaders occupy high-degree nodes in a
heterogeneous network, their ability to motivate fairness
among neighboring proposers is amplified, and collective
fairness is facilitated. We propose an evolutionary game model
and an agent-based simulation framework that capture the
microscopic mechanisms underlying the networked experiments.
Our experiments, model, and simulations suggest that network
reciprocity is achievable but requires coordinated
interactions between different prosocial inclinations
<br>
of individuals and social network structures.
<br>
<br>
</blockquote>
<br>
<br>
</blockquote>
<br>
</blockquote>
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