Going That Extra Mile: Individuals Travel Further to Maintain Face-to-Face Contact with Highly Related Kin than with Less Related Kin
Dunbar RIM (2013) Going That Extra Mile: Individuals Travel Further to Maintain Face-to-Face Contact with Highly Related Kin
than with Less Related Kin. PLoS ONE 8(1): e53929. doi:10.1371/journal.pone.0053929
Going That Extra Mile: Individuals Travel Further to Maintain Face-to-Face Contact with Highly Related Kin than with Less Related Kin
Thomas V. Pollet 0
Sam G. B. Roberts 0
Robin I. M. Dunbar 0
Ronald Noe, Universite de Strasbourg, France
0 1 Department of Social and Organizational Psychology, VU University Amsterdam , Amsterdam , The Netherlands , 2 Department of Psychology, University of Chester, Chester, United Kingdom, 3 Department of Experimental Psychology, University of Oxford , Oxford , United Kingdom
The theory of inclusive fitness has transformed our understanding of cooperation and altruism. However, the proximate psychological underpinnings of altruism are less well understood, and it has been argued that emotional closeness mediates the relationship between genetic relatedness and altruism. In this study, we use a real-life costly behaviour (travel time) to dissociate the effects of genetic relatedness from emotional closeness. Participants travelled further to see more closely related kin, as compared to more distantly related kin. For distantly related kin, the level of emotional closeness mediated this relationship - when emotional closeness was controlled for, there was no effect of genetic relatedness on travel time. However, participants were willing to travel further to visit parents, children and siblings as compared to more distantly related kin, even when emotional closeness was controlled for. This suggests that the mediating effect of emotional closeness on altruism varies with levels of genetic relatedness.
Funding: Thomas Pollet is supported by The Netherlands Organisation for Scientific Research (Veni, 451.10.032). Robin Dunbar is supported by an ERC grant
(Psychology of Relationships, Networks and Community Cohesion). The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Inclusive fitness theory  has proved fundamental in
explaining patterns of cooperation and altruism across a wide
range of species [2,3], including humans [4,5] Hamiltons rule of
kin selection states that a behaviour or trait will be favoured by
selection when r*B.C, where C is the fitness cost to the actor, B is
the fitness benefit to the recipient and r is the coefficient of genetic
relatedness the probability that two individuals share the same
genes by descent . Since the benefit of an action to the recipient
is weighted by the coefficient of genetic relatedness, all other things
being equal, more closely related individuals (with a higher r) are
predicted to be favoured over less closely related individuals (with
a lower r). In line with this theorys predictions, people offer
greater levels of support to more closely related kin members, both
in hypothetical (e.g., ) and real-life situations (e.g., [9,10]).
However, whilst people broadly appear to act in line with
inclusive fitness theory in distributing support amongst kin, the
proximate psychological mechanisms underlying this behaviour
are much less clear. In particular, the extent to which these
finegrained distinctions between kin of different relatedness are driven
directly by knowledge of the genetic relatedness, and the degree to
which they are mediated by other relationship variables, is a
matter of intense debate . Korchmaros and Kenny [13,14]
argue that emotional closeness is an important proximal cause for
altruism towards kin. Emotional closeness is a widely used concept
in social psychology , and previous definitions of emotional
closeness have included concepts such as a sense of shared
experience, concern for and trust of another individual, enjoyment
of the relationship  and a feeling of support, willingness and
confidence to disclose very personal feelings and the explicit
willingness to place value on the relationship . People tend to
spend time, have frequent contact with and therefore form
emotionally close relationships with more closely related kin, and
Korchmaros and Kenny presented evidence that the level of
emotional closeness mediates the relationship between kinship
categories (which were then converted into genetic relatedness)
and altruism [13,14]. In contrast, other findings have led to
suggestions that there may be a kinship premium , in that
kinship (as a purely linguistic label that correlates with true
biological kinship) makes a significant unique contribution to
altruism, even after controlling for the effects of emotional
closeness (see also ).
Further, previous studies investigating the psychological
mechanisms underpinning kinship have tended to treat kinship as a
unified category [11,13,2022], in that the same mechanisms (e.g.
the kinship premium, mediation via emotional closeness) are
proposed to operate equally across all kin categories. However,
given the fundamental importance of the coefficient of relatedness
in shaping behaviour towards kin, it is possible that the
mechanisms operate in distinct ways for different categories of
kin. For example, a long period of co-residence, or maternal
perinatal association, may trigger distinct psychological
mechanisms towards parents and siblings (r = 0.5) that are not triggered
for less closely related kin (e.g., ). Thus, the mediation with
emotional closeness [13,14] or the kinship premium  may not
operate in a uniform way across all kin, but operate differently in
kin with different degrees of relatedness.
The purpose of this study is to test whether emotional closeness
mediates the relationship between genetic relatedness and
investment in a kin relationship, using a real-life costly behaviour
(distance travelled to visit a relative). We also examine whether
emotional closeness mediates the relationship between genetic
relatedness and investment in a kin relationship in the same way
for kin with different levels of relatedness. Previous research that
has controlled for the effect of emotional closeness on investment
in kin has typically been based on hypothetical scenarios (for
example [6,8,24]), raising doubts as to how well such responses
mirror actual behaviour [25,26]. Where research has been based
on real-life behaviour [27,28], it is unclear whether the results
were driven directly by genetic relatedness (i.e. individuals lend
support to others solely based on their kinship classification
parent, sibling, cousin etc.) or indirectly by emotional closeness,
since these have invariably been confounded .
In this study, we combine these two approaches and examine
how physical separation influences willingness to travel to see
genetic relatives as a function of relatedness, and whether this is
mediated by emotional closeness. Travel time has a genuine cost:
travelling further costs more both in time (which is an inelastic
resource, ) and also money. Although it is likely that both
parties benefit from meeting, the cost of travel is asymmetric
between the two parties. Hence, although we could frame our
study either as a case of cooperative investment (both parties invest
to facilitate cooperation)  or, given the positive effects of social
relationships on health and well-being , a case of altruism (one
party pays a cost to benefit the other ), depending on how the
benefits are costed, we prefer to focus explicitly on the asymmetry
in costs paid. Thus, in this study, we simply examine whether
individuals are prepared to pay higher costs to visit some relatives,
as opposed to others, in order to keep the relationship active.
Keeping kin relationships active has been found to have positive
effects on the financial and emotional support for, as well as the
health of, ones offspring . We hypothesize that people will
travel further to see more closely related kin, than more distantly
related kin. We also examine whether this relationship is mediated
by emotional closeness. If investment in a relationship is mediated
by emotional closeness, then after controlling for emotional
closeness there should be no significant effect of genetic relatedness
on willingness to travel. In contrast, if there is a kinship premium
 there should still be a significant effect of genetic relatedness
on willingness to travel, even after controlling for emotional
Materials and Methods
355 participants, 72% German and 28% Dutch, were recruited
via the University of Groningen. The sample consisted of 67%
women, with a mean age of 29 years (SD = 13.63 years). Most of
the respondents did not (yet) have a university degree (85%
without university degree).
In order to obtain a larger non-student sample, participants
were recruited via the personal networks of students. This method
has been used successfully in previous studies (e.g. [15,35]).
Students completed a questionnaire and were instructed to hand
out surveys to friends, colleagues and family. Surveys were
returned in sealed envelopes. In order to avoid potential overlap,
students were instructed not to hand out surveys to other students
from the same degree as themselves. Students received course
credits in return for completing this task (return rate .85%). The
study was approved by the psychology ethics committee where the
study was carried out.
Participants first provided some basic sociodemographic data,
including age, gender, nationality and educational attainment.
They then listed the initials of all their living relatives and specified
their kin category (parent, child, full sibling, etc.), and whether
they were biological kin, step, affinal or adopted. Given that less
than 2.5% of relatives listed were step, affinal or adopted, we
excluded these categories. Our sample thus only contained
biological kinship ties (4,867 kinship ties). On average, individuals
listed 14 biological kin (SD = 8.37).
For each reported biological relationship, we coded the
coefficient of relatedness . There were four categories:
r = 0.5 (siblings, parents, children), r = 0.25 (half-siblings, nieces/
nephews, grandparents, uncles and aunts), r = 0.125 (first cousins,
great-grandparents, great-uncles, great-aunts), r = 0.03125 (second
Participants classified their last face-to-face contact with each
relative in terms of six categories (within last 2 days (1); 37 days
ago (2); 814 days ago (3); 1530 days ago (4); over a month ago
(5); never (6)). Previous work on social networks has consistently
identified at least two distinct types of social ties (sometimes called
core and significant ties), with differing degrees of emotional
strength and which offer differing degrees of emotional and
material support . These closest core ties have also been
referred to as the support group, which consists of around five
individuals, from whom one would solicit help in times of personal
crisis . The less emotional intense significant ties have been
referred to as the sympathy group, which consists of around
fifteen individuals, inclusive of the support group, and can be
defined as those individuals whose sudden death would be greatly
upsetting [42,43]. In turn, the support and sympathy group
overlap roughly with weekly and monthly face-to-face contact
Since these two groups of social ties have different properties, it
is possible that emotional closeness may mediate the relationship
between kinship and willingness to travel differently in the support
and sympathy groups. For example, it may be that willingness to
travel is more reliant on kinship for the weaker ties in the
sympathy group, but more dependent on emotional closeness for
the stronger ties in the support group. Thus, for the purposes of
our analyses, we simplified our categories of last contact into
weekly contact (merged categories 12) and monthly contact
(merged categories 14), as they overlap with the definitions of the
support and sympathy group , and investigated the effect of
emotional closeness on willingness to travel separately for these
In this study, we focus on face-to-face contact, as this has a
genuine cost in travel time in a way that non-face-to-face contact
(via e-mail, telephone etc.) does not. However, previous research
on media multiplexity has demonstrated that the frequency of
non-face-to-face communication is closely tied to the frequency of
face-to-face communication  particularly for mobile phone use
[45,46]. Further, the level of emotional closeness is closely related
to the frequency of both face-to-face and non face-to-face
Distance was measured as how long (in minutes) it took the
participant to travel to meet the contact, as reported by the
participant (Minimum: 1; Maximum: 4800 mins; Table 1).
Participants were instructed to list 0 mins. for individuals who
were living with them, so cohabiting family were excluded. All
responses greater than 1440 mins. (24 h) were recoded to a
standard 1440 mins. We chose time, rather than a measure in
kilometres, as our previous work suggests that individuals find it
easier to estimate time rather than distance for network ties
Respondents also listed how emotionally close they felt to each
biological relative on a scale from 1 to 10 (with 10 being very
close). The (translated) question was formulated as follows: On a
scale of 110 (where 10 is very close) please say how close the person
is to you in terms of how you feel about them. Very rarely participants
listed 0, we have chosen to keep these data in the dataset (N = 48;
1% of total data). A single-item measure of emotional closeness has
been used in a large number of previous studies by different
research groups [1315,4850] and is simple for participants to
answer for a large number of network members. Further, a
measure of emotional closeness has been shown to be the most
reliable indicator of tie strength, as compared to other measures
such as the duration of the relationship, the frequency of contact
or the type of the relationship .
After reporting the descriptive statistics of our sample, we
present the results of stratified Cox regression models, also known
as stratified proportional hazard models  (see [56,57] for
examples of Cox regression models). This technique allows us to
test whether, with increasing distance, more closely related
individuals are more likely to maintain contact than more distantly
related individuals. Cox regression is typically used to analyze the
likelihood of survival over time , but has also been used to
investigate the likelihood of an event, here, maintaining contact
with increasing distance . As detailed above, we built separate
models for weekly and monthly contact (respectively: codes 12
and codes 1,2,3,4 coded as event). As is standard practice with Cox
regression models, kin members contacted over a month ago or
never were included in the models.
between 3 and 7 days ago
between 8 and 14 days ago
between 15 and 30 days ago
over a month ago
(score from 0 to 10)
Cox regression makes relatively few assumptions compared to
other statistical techniques, but a key one, which we tested, is the
proportional hazard assumption. In our case, the key variables of
interest (coefficient of relatedness, emotional closeness) should not
be related to travel time . Rephrased, it is possible that the
relationship between willingness to travel and relatedness and/or
emotional closeness is driven by a spurious relationship with
distance. If this is the case then there will be evidence for
significant distance6relatedness and/or distance6emotional
closeness covariates and the model can be appropriately adjusted
by including such a distance-dependent covariate.
Stratified Cox regression generates a hazard function for each
participant and thus takes into account the nested structure of the
data (multiple kinship ties are nested within each participant, and
thus each kinship tie cannot be treated as an independent data
point). We report coefficients from the Cox regression, the hazard
ratios (Exp(B)) and the Wald statistics. For ease of interpretation,
all coefficients were recoded in the same direction, so that a hazard
ratio larger than 1 means a greater willingness to travel further to
visit more closely related kin, as compared to more distantly
related kin. A hazard ratio smaller than 1 means a greater
willingness to travel further to visit more distantly related kin as
compared to more closely related kin.
There were no control variables (such as nationality, age or
gender) at participant level as these variables were either constant
or a linearly dependent function of the stratum effect. For
graphical representation, we present the aggregated data: the
cumulative likelihood of travelling further by varying degrees of
relatedness (rather than these functions for every single individual).
As detailed above, we built separate models for weekly and
All analyses were conducted in SPSS 16.0  and more details
on the algorithms for (stratified) Cox Regression can be found in
the SPSS manual  or in the cited works above.
MODEL 1 (22LL = 5096)
MODEL 2 (22LL = 4878)
(B = coefficient; SE = standard error; Wald = Wald test statistic; Exp(B) = Hazard ratio; p = p value associated with Wald test).
Table 1 gives the descriptive statistics for all variables used in
Maintaining contact at least weekly
Model 1 shows the coefficients for every comparison between
categories of relatedness (Table 2). The Exp(B) in the tables are the
hazard ratios. These can be converted into probabilities using the
formula: probability = Exp(B)/(1+Exp(B)) . For example, a
hazard ratio of 11.36 (comparison of r = .5 to r = .032; Table 2),
means that in 92% of the cases, individuals related at r = .5
travelled further to maintain weekly contact than those of who are
related with r = .03. The coefficients for all the comparisons, with
the exception of r = .03 vs. r = .125, were significant and sizeable.
Figure 1 displays the pattern graphically: for weekly contact,
individuals were more likely to travel further to visit more closely
related kin, as compared to more distantly related kin.
Model 1 could not be improved by adding a distance-dependent
covariate (distance6coefficient relatedness: p..1; see Text S1)
Model 2 includes the participants rating of emotional closeness
to the individual concerned (known as a tie in network
terminology). Overall, participants were willing to travel further
to maintain contact with those who are emotionally closer to them
(Exp(B) = 1.37; p,.0001). However, only the comparisons with
r = .5 and other kin categories remained significant. Individuals
were significantly more likely to travel to maintain weekly contact
with those of r = .5, as compared to other categories of relatedness,
even when emotional closeness is controlled for. Other
comparisons between categories in Model 2 were no longer significant.
This suggests that emotional closeness mediates the willingness to
travel further to keep weekly contact for these kin categories.
Given that the coefficients for r = .5 in comparison to other
categories of kin remain significant, whereas for other comparisons
between kin categories the coefficients became non-significant, it
appears that parent-offspring and full sibling ties are substantially
different from other biological kinship ties (such as grandparents or
cousins), even after taking into account the level of emotional
Model 2 could be slightly improved by including a
distance6emotional closeness interaction (Wald = 5.299; p = .021). A model
with this interaction yielded a slightly stronger hazard ratio for
emotional closeness than those reported in Table 2 (Exp(B) = 1.42).
The significance and size of the other effects remained virtually
Maintaining contact at least once a month
Model 3 shows the coefficients for every comparison between
categories of relatedness (Table 3; Figure 2). All coefficients, with
the exception of r = .03 vs. r = .125, were significant and sizeable.
The coefficient of r = .03 vs. r = .125 was, however, marginally
significant (p = .06) and in the predicted direction. Figure 2
displays the pattern graphically for monthly contact: participants
were more likely to travel further to visit more closely related kin,
as compared to more distantly related kin. Model 3 could not be
Figure 1. Cumulative likelihood of maintaining weekly contact (Table 2, Model 1), aggregated data.
improved by adding a distance6coefficient of relatedness
interaction (p..1; see Text S1).
As with Model 2 for weekly contact, in Model 4 highly related
kin (r = .5) were willing to travel further to maintain monthly
contact than more distantly related kin, even after controlling for
emotional closeness. The only other significant comparison was
between r = .25 and r = .125. As with Model 2, in Model 4 the
coefficients were greatly reduced in size, suggesting that emotional
closeness mediates the effect of relatedness on the willingness to
travel to keep in contact.
Model 4 could be slightly improved by adding a
distance6emotional closeness interaction (Wald = 4.098; p = .043). This leads to a
slightly stronger effect of emotional closeness (Exp(B) = 1.32). The
comparisons for different categories of relatedness remain virtually
Here, we provide the first test of the hypothesis that emotional
closeness mediates the relationship between genetic relatedness
and investment in kin using a real-life costly behaviour (travel
time). In doing so, we integrate evolutionary theory and social
psychology by exploring how inclusive fitness theory is mediated
by psychological variables. There were three key results. First,
exactly in line with predictions derived from inclusive fitness
theory , individuals were willing to travel for longer to see more
closely related kin (e.g. to see a parent or sibling, compared to an
uncle or aunt). Second, when emotional closeness was included in
the models, the comparisons between all categories of kin except
for parents/children/siblings (r = .5) were strongly reduced in size
and no longer significant, suggesting that the relationship between
genetic relatedness and willingness to travel is mediated by
emotional closeness for distantly related kin. Finally, and most
importantly, even when controlling for emotional closeness,
individuals were still willing to travel significantly further to see
their closest relatives (r = .5) as compared to any other relatives.
In part, our results support the hypothesis that emotional
closeness acts as a crucial mediating variable between genetic
relatedness and altruism [13,14]. Thus, willingness to travel
further or for longer to see more distantly related kin appears to be
driven by emotional closeness, rather than genetic relatedness:
when emotional closeness was controlled for, the differences
between distantly related kin were no longer significant. However,
the results also add a crucial caveat to this hypothesis, namely that
the mediating effect of emotional closeness appears to act
differentially with respect to the level of genetic relatedness, with
a clear distinction between the closest kin and more distant kin.
Thus, our results suggest that rather than the psychological
mechanisms underpinning kinship acting equally on all types of
kin, in fact these psychological mechanisms may be distinct for
different categories of kin and not be fully explained by emotional
closeness. Emotional closeness appears to mediate investment for
distantly related kin [13,14], but there is a residual kinship
premium  for the most closely related kin. Future research
could use the memory confusion paradigm  to examine
whether people form separate implicit concepts of close and
In this study, we used the variable emotional closeness to
measure the strength of the social bond between two individuals.
This measure has been widely used in social psychology [14
18,26], is the most reliable indicator of tie strength  and
correlates highly with self-reported altruism . However,
despite its wide use, there is no definitive definition of emotional
closeness (see e.g.,  p. 17), and future work could usefully
unpack the one-dimensional concept of emotional closeness in
more detail. Further, the single-item measure of emotional
MODEL 3 (22LL = 8728)
MODEL 4 (22LL = 8471)
(22LL = 22LogLikelihood of the model; B = coefficient; SE = standard error; Wald = Wald test statistic; Exp(B) = Hazard ratio; p = p value associated with Wald test).
closeness used in this and many other studies [1315,50,62,63]
may be a somewhat imprecise measure of the emotional intensity
of the relationship, as compared to more detailed assessments of
the relationship, for example based on interviews (e.g., ). The
fact that this somewhat imprecise and noisy measure mediated
most of the relationship between the degree of relatedness and
willingness to travel lends support to the theory that emotional
closeness is an important mediator of altruism to kin, with the
crucial exception of the most closely related kin (r = .5).
In relation to cooperation and altruism, it may be that
emotional closeness tracks the degree to which past altruistic
behaviour has been reciprocated, i.e. whether the cost of the
altruistic behaviour has been balanced by the benefits received
. Thus, emotional closeness may be a component of
attitudinal reciprocity  or emotional bookkeeping  as
used in the animal literature, particularly given the working
memory constraints of keeping track of past interactions [67,68].
Moreover there might be other cues to kinship which could be
specific to certain kinship ties. Lieberman and colleagues have
argued for example that both co-residence duration and the
maternal perinatal association are particularly important for kin
recognition among siblings . Other research has pointed to the
role of facial resemblance for kin recognition (e.g., [21,69,70]
review in ) and the role of psychological similarity (e.g., ).
These other cues to kinship, such as physical and psychological
similarity, could be driving the difference between close kin (r = .5)
as opposed to other kin categories and which cue is predominant
could be contingent on many factors, such as sex (e.g., ) and
type of kin (e.g., [23,74]). Moreover these kinship cues could
interact as suggested by work on sexual imprinting: a preference
for a self-resembling partner can be a function of the relationship
with ones parents (e.g., [75,76], but see ).
Whilst this study benefitted from the use of a large non-student
sample , it did have some limitations. First, it is possible that
the difference between parent-child and sibling relationships
versus other kinship relationships found in our study are due to
the uni-dimensional nature of our measure of emotional closeness.
On the other hand, as outlined above, it is actually all the more
surprising that a uni-dimensional measure mediates most of the
relationship between relatedness and willingness to travel.
Nonetheless, further research is necessary into the proximate
factors beyond emotional closeness affecting the likelihood of
visiting kin of different levels of genetic relatedness. For example,
perceived obligation varies with genetic relatedness and has been
shown to influence helping behaviour towards kin . Second,
participants were asked to self-report travel time and journeys of
the same travel time may have different monetary costs, depending
on the mode of transport used. Third, there are other factors,
apart from biological relatedness, that influence the willingness to
travel to meet up with certain kin, which we did not measure such
as, for example, how rewarding the visit is, or whether the kin are
matrilineal or patrilineal (e.g., ). Fourth, the current research,
did not investigate who initiates contact which is asymmetric for
many kinship categories (e.g. parent-offspring,
grandparentgrandchild). For many kinship categories, there are differences in
reproductive value (the expected future contribution to ones
Figure 2. Cumulative likelihood of maintaining monthly contact (Table 3, Model 3), aggregated data.
fitness ), and reproductive value has been shown to predict
asymmetries in kin investment among humans . For example,
childless individuals report feeling closer to nieces/nephews than
to aunts/uncles . In certain cases, reproductive value will be
an even more important factor for kin investment than biological
relatedness (e.g. ). Nonetheless, all else being equal, from an
ultimate perspective we expect individuals to discriminate between
kin relationships which differ according to the coefficient of
relatedness and our data suggest this is indeed the case in this
sample. Fifth, it is possible that there are some limitations inherent
to our statistical analyses. One issue could be that our model
assumes statistical independence in contact and that in reality
when individuals have contact with several kin at the same time
(for example for Easter, a baptism or a birthday). This is indeed
possible, but if it was driving the effect, then it should have made it
harder to find the effects for relatedness in Models 1 and 3. In
addition, the number of events (weekly or monthly contact) per
individual might have been relatively low, which could potentially
lead to biases in the stratified Cox regression test statistics.
However, a low frequency likely would increase Type 1 errors
making it harder to find the results detailed above, and simulations
suggest that Cox regression performs relatively well even when the
number of events are low .
Finally, our correlational design cannot indicate the
directionality of the relationship between emotional closeness and
investment in kin: does contact with kin lead to emotional
attachment, or does emotional attachment lead to contact?
Previous longitudinal research has suggested that contact
frequency and emotional closeness are very closely temporally linked ,
so fine grained data using electronic communication records (e.g.,
mobile phone records ) may be more effective at disentangling
these two possibilities than even longitudinal questionnaire studies.
Further studies are clearly needed in order to fully understand the
dynamics of investment in kin relationships.
In this paper, we examined a real-life costly behaviour and
demonstrated that for distantly related kin, emotional closeness
mediated the relationship between genetic relatedness and
willingness to travel. However, even when controlling for
emotional closeness, individuals were still willing to travel
significantly further to see their closest relatives (parents, children
and siblings), as compared to any other relatives. Thus, the way in
which emotional closeness mediates investment appears to operate
differently across different kinship categories, in that it has a
stronger mediating effect on distantly related kin, as compared to
more closely related kin.
The authors thank the participants who took part in this research, Jana
Niemann for assistance with translation, research assistants at Groningen
for their help with processing the data and participants at the HBES
conference for feedback on this work. The data were collected while
Thomas Pollet was at the University of Groningen. The authors thank the
editor and two anonymous referees for comments which helped to
substantially improve earlier versions of this paper.
Conceived and designed the experiments: TVP SGBR RIMD. Performed
the experiments: TVP. Analyzed the data: TVP. Wrote the paper: TVP
1. Hamilton WD ( 1964 ) Genetical evolution of social behaviour 1 . Journal of Theoretical Biology 7 : 1 - 16 .
2. Bourke AFG ( 2011 ) The validity and value of inclusive fitness theory . Proceedings Of The Royal Society B: Biological Sciences 278 : 3313 - 3320 . doi:10.1098/rspb.2011.1465.
3. West SA , Griffin AS , Gardner A ( 2007 ) Evolutionary explanations for cooperation . Current Biology 17 : R661 - R672 .
4. Barrett L , Dunbar RIM , Lycett J ( 2002 ) Human Evolutionary Psychology . Basingstoke: Palgrave.
5. West SA , Mouden C , Gardner A ( 2011 ) Sixteen common misconceptions about the evolution of cooperation in humans . Evolution and Human Behavior 32 : 231 - 262 . doi:10.1016/j.evolhumbehav. 2010 .08.001.
6. Burnstein E , Crandall C , Kitayama S ( 1994 ) Some Neo-Darwinian decision rules for alturism - weighing cues for inclusive fitness as a function of the biological importance of the decision . Journal of Personality and Social Psychology 67 : 773 - 789 .
7. Rachlin H , Jones BA ( 2008 ) Altruism among relatives and non-relatives . Behavioural Processes 79 : 120 - 123 . doi:10.1016/j.beproc. 2008 .06.002.
8. Stewart-Williams S ( 2007 ) Altruism among kin vs. nonkin: effects of cost of help and reciprocal exchange . Evolution and Human Behavior 28 : 193 - 198 .
9. Madsen EA , Tunney RJ , Fieldman G , Plotkin HC , Dunbar RIM , et al. ( 2007 ) Kinship and altruism: A cross-cultural experimental study . British Journal of Psychology 98 : 339 - 359 .
10. Smith MS , Kish BJ , Crawford CB ( 1987 ) Inheritance of wealth as human kin investment . Ethology and Sociobiology 8 : 171 - 182 . doi:10.1016/ 0162 - 3095(87)9004 2 .
11. Ackerman JM , Kenrick DT , Schaller M ( 2007 ) Is friendship akin to kinship? Evolution and Human Behavior 28: 365 - 374 . doi:10.1016/j.evolhumbehav. 2007 .04.004.
12. Curry O , Roberts SGB , Dunbar RIM ( 2012 ) Altruism in social networks: Evidence for a ''kinship premium'' . British Journal of Psychology . doi:10.1111/ j.2044- 8295 . 2012 .02119.x. Advance Online Publication.
13. Korchmaros JD , Kenny DA ( 2001 ) Emotional closeness as a mediator of the effect of genetic relatedness on altruism . Psychological Science 12 : 262 - 265 .
14. Korchmaros JD , Kenny DA ( 2006 ) An evolutionary and close-relationship model of helping . Journal of Social and Personal Relationships 23 : 21 - 43 . doi:10.1177/0265407506060176|issn 0265 - 4075 .
15. Roberts SGB , Dunbar RIM , Pollet TV , Kuppens T ( 2009 ) Exploring variation in active network size: Constraints and ego characteristics . Social Networks 31 : 138 - 146 . doi:10.1016/j.socnet. 2008 .12.002.
16. Roberts SGB , Dunbar RIM ( 2011 ) The costs of family and friends: An 18- month longitudinal study of relationship maintenance and decay . Evolution and Human Behavior 32 : 186 - 197 . doi:10.1016/j.evolhumbehav. 2010 .08.005.
17. Parks MR , Floyd K ( 1996 ) Meanings for Closeness and Intimacy in Friendship . Journal of Social and Personal Relationships 13 : 85 - 107 . doi:10.1177/ 0265407596131005.
18. Lee TR , Mancini JA , Maxwell JW ( 1990 ) Sibling relationships in adulthood: Contact patterns and motivations . Journal of Marriage and the Family : 431 - 440 .
19. Kruger DJ ( 2003 ) Evolution and altruism - Combining psychological mediators with naturally selected tendencies . Evolution and Human Behavior 24 : 118 - 125 .
20. Curry O , Dunbar RIM ( 2011 ) Altruism in networks: the effect of connections . Biology Letters 7 : 651 - 653 .
21. DeBruine LM ( 2005 ) Trustworthy but not lust-worthy: context-specific effects of facial resemblance . Proceedings Of The Royal Society B: Biological Sciences 272 : 919 - 922 . doi:10.1098/rspb.2004.3003.
22. Lieberman D , Oum R , Kurzban R ( 2008 ) The family of fundamental social categories includes kinship: Evidence from the memory confusion paradigm . European Journal of Social Psychology 38 : 998 - 1012 . doi:10.1002/ejsp.528.
23. Lieberman D , Tooby J , Cosmides L ( 2007 ) The architecture of human kin detection . Nature 445 : 727 - 731 .
24. Rachlin H , Jones BA ( 2008 ) Altruism among relatives and non-relatives . Behavioural Processes 79 : 120 - 123 . doi:10.1016/j.beproc. 2008 .06.002.
25. Ben-Ner A , Kramer A , Levy O ( 2008 ) Economic and hypothetical dictator game experiments: Incentive effects at the individual level . Journal of Socio-Economics 37 : 1775 - 1784 . doi:10.1016/j.socec. 2007 .11.004.
26. West SG , Jan Brown T ( 1975 ) Physical attractiveness, the severity of the emergency and helping: A field experiment and interpersonal simulation . Journal of Experimental Social Psychology 11 : 531 - 538 . doi:10.1016/ 0022 - 1031(75) 9 .
27. Grayson DK ( 1993 ) Differential mortality and the Donner Party disaster . Evolutionary Anthropology 2 : 151 - 159 .
28. Shavit Y , Fischer CS , Koresh Y ( 1994 ) Kin and nonkin under collective threat: Israeli networks during the gulf war . Social Forces 72 : 1197 - 1215 .
29. Neyer FJ , Lang FR ( 2003 ) Blood is thicker than water: Kinship orientation across adulthood . Journal of Personality and Social Psychology 84 : 310 - 321 . doi:10.1037/ 002 - 3514 .84.2.310|issn 0022 - 3514 .
30. Nie NH ( 2001 ) Sociability, Interpersonal Relations , and the Internet . American Behavioral Scientist 45 : 420 - 435 . doi:10.1177/00027640121957277.
31. Noe R ( 2006 ) Cooperation experiments: coordination through communication versus acting apart together . Animal Behaviour 71 : 1 - 18 . doi:10.1016/ j.anbehav. 2005 .03.037.
32. Holt-Lunstad J , Smith TB , Layton JB ( 2010 ) Social relationships and mortality risk: A meta-analytic review . PLoS Medicine 7. doi:10.1371/journal.pmed.1000316.
33. West SA , Griffin AS , Gardner A ( 2007 ) Social semantics: altruism, cooperation, mutualism, strong reciprocity and group selection . Journal of Evolutionary Biology 20 : 415 - 432 .
34. Kana'Iaupuni SM , Donato KM , Thompson-Colon T , Stainback M ( 2005 ) Counting on kin: Social networks, social support, and child health status . Social Forces 83 : 1137 - 1164 .
35. Pollet T V , Roberts SGB , Dunbar RIM ( 2011 ) Extraverts Have Larger Social Network Layers . Journal of Individual Differences 32 : 161 - 169 . doi:10.1027/ 1614 - 0001 /a000048.
36. Wright S ( 1922 ) Coefficients of inbreeding and relationship . American Naturalist 56 : 330 - 338 .
37. Binder JF , Roberts SGB , Sutcliffe AG ( 2012 ) Closeness, loneliness, support: Core ties and significant ties in personal communities . Social Networks 34 : 206 - 214 . doi:10.1016/j.socnet. 2011 .12.001.
38. Boase J , Horrigan JB , Wellman B , Rainie L ( 2006 ) The strength of internet ties . Pew Report.
39. Wellman B , Wortley S ( 1990 ) Different strokes from different folks: community ties and social support . American Journal of Sociology 96 : 558 - 588 .
40. Dunbar RIM , Spoors M ( 1995 ) Social Networks, support cliques and kinship . Human Nature - An Interdisciplinary Biosocial Perspective 6 : 273 - 290 .
41. Stiller J , Dunbar RIM ( 2007 ) Perspective-taking and memory capacity predict social network size . Social Networks 29 : 93 - 104 .
42. Binder JF , Roberts SGB , Sutcliffe AG ( 2012 ) Closeness, loneliness, support: Core ties and significant ties in personal communities . Social Networks 34 : 206 - 214 . doi:10.1016/j.socnet. 2011 .12.001.
43. Buys CJ , Larson KL ( 1979 ) Human Sympathy Groups . Psychological Reports 45 : 547 - 553 . doi:10.2466/pr0.1979. 45 .2. 547 .
44. Haythornthwaite C ( 2005 ) Social Networks and Internet Connectivity Effects. Information, Communication and Society 8.
45. Eagle N , Pentland AS , Lazer D ( 2009 ) Inferring friendship network structure by using mobile phone data . Proceedings of the National Academy of Sciences 106 : 15274 - 15278 .
46. Kim H , Kim GJ , Park HW , Rice RE ( 2007 ) Configurations of Relationships in Different Media: FtF , Email, Instant Messenger , Mobile Phone, and SMS. Journal of Computer-Mediated Communication 12 : 1183 - 1207 . doi:10.1111/ j.1083- 6101 . 2007 .00369.x.
47. Pollet T V , Kuppens T , Dunbar RIM ( 2006 ) When nieces and nephews become important: Differences between childless women and mothers in relationships with nieces and nephews . Journal of Cultural and Evolutionary Psychology 4 : 83 - 93 .
48. Cummings JN , Lee JB , Kraut R ( 2006 ) Communication technology and friendship during the transition from high school to college . In: Kraut K, Brynin M , Kiesler S , editors. Computers, phones and the internet: Domesticating information technologies . New York : Oxford University Press . pp. 265 - 278 .
49. Hill RA , Dunbar RIM ( 2003 ) Social network size in humans . Human Nature-An Interdisciplinary Biosocial Perspective 14 : 53 - 72 .
50. Jeon J , Buss DM ( 2007 ) Altruism towards cousins . Proceedings of the Royal Society B: Biological Sciences 274 : 1181 - 1187 . doi:10.1098/rspb.2006.0366.
51. Marsden P V , Campbell KE ( 1984 ) Measuring tie strength . Social forces 63 : 482 - 501 .
52. Cox DR ( 1972 ) Regression models and life-tables . Journal of the Royal Statistical Society Series B (Methodological) : 187 - 220 .
53. Allison P ( 1984 ) Event history analysis: Regression for longitudinal event data . London: Sage Publications, Incorporated.
54. Lee ET , Wang JW ( 2003 ) Statistical methods for survival data analysis . Hoboken , NJ: Wiley-Interscience.
55. Kalbfleisch JD , Prentice RL ( 2002 ) Relative Risk (Cox) Regression Models . In: Kalbfleisch JD, Prentice RL, editors. The Statistical Analysis of Failure Time Data. Hoboken , NJ: John Wiley & Sons, Inc. pp. 95 - 147 .
56. Adams G ( 1996 ) Using a Cox regression model to examine voluntary teacher turnover . The Journal of Experimental Education 64 : 267 - 285 . doi:10.1080/ 00220973.1996.9943807.
57. Simons MJP , Briga M , Koetsier E , Folkertsma R , Wubs MD , et al. ( 2012 ) Bill Redness Is Positively Associated with Reproduction and Survival in Male and Female Zebra Finches . PLoS ONE 7 : e40721 .
58. Pollet T V , Nettle D , Nelissen M ( 2007 ) Maternal grandmothers do go the extra mile: Factoring distance and lineage into differential contact with grandchildren . Evolutionary Psychology: an international journal of evolutionary approaches to psychology and behavior 5 : 832 - 843 .
59. SPSS ( 2007 ) SPSS for Windows 16 .0.
60. SPSS ( 2007 ) SPSS 16.0 User Manual .
61. Spruance SL , Reid JE , Grace M , Samore M ( 2004 ) Hazard ratio in clinical trials . Antimicrobial Agents and Chemotherapy 48 : 2787 - 2792 .
62. Cummings JN , Lee JB , Kraut R ( 2006 ) Communication technology and friendship during the transition from high school to college . In: Kraut K, Brynin M , Kiesler S , editors. Computers, phones and the internet: Domesticating information technologies . New York : Oxford University Press . pp. 265 - 278 .
63. Hill RA , Dunbar RIM ( 2003 ) Social network size in humans . Human Nature-An Interdisciplinary Biosocial Perspective 14 : 53 - 72 .
64. Hogan B , Carrasco JA , Wellman B ( 2007 ) Visualizing personal networks: Working with participant-aided sociograms . Field Methods 19 : 116 - 144 .
65. Brosnan SF , De Waal FBM ( 2002 ) A proximate perspective on reciprocal altruism . Human Nature - An Interdisciplinary Biosocial Perspective 13 : 129 - 152 .
66. Schino G , Aureli F ( 2010 ) The relative roles of kinship and reciprocity in explaining primate altruism . Ecology Letters 13 : 45 - 50 .
67. Stevens JR , Hauser MD ( 2004 ) Why be nice? Psychological constraints on the evolution of cooperation . Trends in Cognitive Sciences 8 : 60 - 65 .
68. Milinski M , Wedekind C ( 1998 ) Working memory constrains human cooperation in the Prisoner's Dilemma . Proceedings of the National Academy of Sciences 95 : 13755 .
69. DeBruine LM , Smith FG , Jones BC , Roberts SC , Petrie M , et al. ( 2009 ) Kin recognition signals in adult faces . Vision Research 49 : 38 - 43 .
70. Bressan P , Zucchi G ( 2009 ) Human kin recognition is self-rather than familyreferential . Biology Letters 5 : 336 - 338 .
71. Krupp DB , DeBruine LM , Jones BC ( 2011 ) Cooperation and Conflict in the Light of Kin Recognition Systems . In: Salmon CA, Shackelford TK, editors. The Oxford Handbook of Evolutionary Family Psychology. Oxford, UK: Oxford University Press, USA. pp. 345 - 362 .
72. Apicella CL , Marlowe FW ( 2004 ) Perceived mate fidelity and paternal resemblance predict men's investment in children . Evolution and Human Behavior 25 : 371 - 378 .
73. Heijkoop M , Dubas JS , Van Aken MAG ( 2009 ) Parent-child resemblance and kin investment: Physical resemblance or personality similarity ? European Journal of Developmental Psychology 6 : 64 - 69 .
74. Pollet T V ( 2007 ) Genetic relatedness and sibling relationship characteristics in a modern society . Evolution and Human Behavior 28 : 176 - 185 .
75. Bereczkei T , Gyuris P , Weisfeld GE ( 2004 ) Sexual imprinting in human mate choice . Proceedings of the Royal Society B: Biological Sciences 271 : 1129 - 1134 .
76. Watkins CD , DeBruine LM , Smith FG , Jones BC , Vukovic J , et al. ( 2011 ) Like father, like self: emotional closeness to father predicts women's preferences for self-resemblance in opposite-sex faces . Evolution and Human Behavior 32 : 70 - 75 .
77. Marcinkowska UM , Rantala MJ ( 2012 ) Sexual imprinting on facial traits of opposite-sex parents in humans . Evolutionary Psychology: an international journal of evolutionary approaches to psychology and behavior 10 : 621 - 630 .
78. Henrich J , Heine SJ , Norenzayan A ( 2010 ) The weirdest people in the world . Behavioral and Brain Sciences 33 : 61 - 83 .
79. Fisher RA ( 1930 ) The genetical theory of natural selection . Oxford, UK: Clarendon Press.
80. Pollet T V , Dunbar RIM ( 2008 ) Childlessness predicts helping of nieces and nephews in United States , 1910 . Journal of Biosocial Science 40 : 761 - 770 .
81. Vittinghoff E , McCulloch CE ( 2007 ) Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression . American Journal of Epidemiology 165 : 710 - 718 .