27 research outputs found
A generic model of dyadic social relationships
We introduce a model of dyadic social interactions and establish its
correspondence with relational models theory (RMT), a theory of human social
relationships. RMT posits four elementary models of relationships governing
human interactions, singly or in combination: Communal Sharing, Authority
Ranking, Equality Matching, and Market Pricing. To these are added the limiting
cases of asocial and null interactions, whereby people do not coordinate with
reference to any shared principle. Our model is rooted in the observation that
each individual in a dyadic interaction can do either the same thing as the
other individual, a different thing or nothing at all. To represent these three
possibilities, we consider two individuals that can each act in one out of
three ways toward the other: perform a social action X or Y, or alternatively
do nothing. We demonstrate that the relationships generated by this model
aggregate into six exhaustive and disjoint categories. We propose that four of
these categories match the four relational models, while the remaining two
correspond to the asocial and null interactions defined in RMT. We generalize
our results to the presence of N social actions. We infer that the four
relational models form an exhaustive set of all possible dyadic relationships
based on social coordination. Hence, we contribute to RMT by offering an answer
to the question of why there could exist just four relational models. In
addition, we discuss how to use our representation to analyze data sets of
dyadic social interactions, and how social actions may be valued and matched by
the agents
Island networks: Transformations of inter-community social relationships in the Lesser Antilles at the advent of European colonialism
The Caribbean Sea was a conduit for human mobility and the exchange of goods and ideas during the whole of its pre-colonial history. The period cal. AD 1000-1800, covering the Late Ceramic Age and early colonial era, represents an archaeologically understudied time during which the Lesser Antilles came under increasing influence from the Greater Antilles and coastal South America and participated in the last phase of indigenous resistance to colonial powers. This article summarizes the results of the Island Network project, supported by the Netherlands Organisation for Scientific Research (NWO) in which a multi-disciplinary set of archaeological, archaeometric, geochemical, GIS, and network science methods and techniques have been employed to disentangle this turbulent era in regional and global history. These diverse approaches reveal and then explore multi-layered networks of objects and people and uncover how Lesser Antillean communities were created and transformed through teaching, trade, migration, movement, and exchange of goods and knowledge
Strong gender differences in reproductive success variance, and the times to the most recent common ancestors
The Time To the Most Recent Common Ancestor (TMRCA) based on human
mitochondrial DNA (mtDNA) is estimated to be twice that based on the
non-recombining part of the Y chromosome (NRY). These TMRCAs have special
demographic implications because mtDNA is transmitted only from mother to
child, and NRY from father to son. Therefore, mtDNA reflects female history,
and NRY, male history. To investigate what caused the two-to-one female-male
TMRCA ratio in humans, we develop a forward-looking agent-based model (ABM)
with overlapping generations and individual life cycles. We implement two main
mating systems: polygynandry and polygyny with different degrees in between. In
each mating system, the male population can be either homogeneous or
heterogeneous. In the latter case, some males are `alphas' and others are
`betas', which reflects the extent to which they are favored by female mates. A
heterogeneous male population implies a competition among males with the
purpose of signaling as alphas. The introduction of a heterogeneous male
population is found to reduce by a factor 2 the probability of finding equal
female and male TMRCAs and shifts the distribution of the TMRCA ratio to higher
values. We find that high male-male competition is necessary to reproduce a
TMRCA ratio of 2: less than half the males can be alphas and betas can have at
most half the fitness of alphas. In addition, in the modes that maximize the
probability of having a TMRCA ratio between 1.5 and 2.5, the present generation
has 1.4 times as many female as male ancestors. We also tested the effect of
sex-biased migration and sex-specific death rates and found that these are
unlikely to explain alone the sex-biased TMRCA ratio observed in humans. Our
results support the view that we are descended from males who were successful
in a highly competitive context, while females were facing a much smaller
female-female competition
Debunking mathematically the logical fallacy that cancer risk is just âbad luckâ
Tomasetti and Vogelstein recently proposed that the majority of variation in cancer risk among tissues is due to âbad luck,â that is, random mutations arising during DNA replication in normal noncancerous stem cells. They generalize this finding to cancer overall, claiming that âthe stochastic effects of DNA replication appear to be the major contributor to cancer in humans.â We show that this conclusion results from a logical fallacy based on ignoring the influence of population heterogeneity in correlations exhibited at the level of the whole population. Because environmental and genetic factors cannot explain the huge differences in cancer rates between different organs, it is wrong to conclude that these factors play a minor role in cancer rates. In contrast, we show that one can indeed measure huge differences in cancer rates between different organs and, at the same time, observe a strong effect of environmental and genetic factors in cancer rates.publishe
Detection of categories of action fluxes in data sets of dyadic interactions.
<p>Patterns of action fluxes expected to be observed in each category. X and Y are social actions belonging to a set of size N. A and B are agents.</p><p>Detection of categories of action fluxes in data sets of dyadic interactions.</p
Six categories of action fluxes.
<p>Exhaustive categorization of relationships in the model of two agents A and B that can each do X, Y or nothing (â
). In elementary interactions, agents can do the same thing or not (i.e. actions can be identical or different) and actions can be null (â
) or not (X or Y). Within the relationship, agents can be able to exchange roles or not.</p><p>Six categories of action fluxes.</p
Nine elementary interactions, simplified.
<p>Same as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120882#pone.0120882.t001" target="_blank">Table 1</a>, with simplified notations for the interactions involving one empty flux.</p><p>Nine elementary interactions, simplified.</p