Abstract
Animal ethologists suggest that non-human primates console victims of aggression in a manner similar to humans. However, the empirical basis for this cross-species comparison is fragile, given that few studies have examined consolation behavior among humans. To address this gap, we revive and apply the underappreciated ethological branch of micro-sociology, which advocates the study of human interactions by applying ethological observation techniques. We thus systematically observed naturally occurring human consolation captured by video surveillance cameras in the aftermath of violent public assaults. Consistent with prior human and non-human primate research, social affiliation promoted consolatory helping. By contrast, we found no main effect of sex. A further exploratory analysis indicated an interaction effect between social affiliation and sex, with female affiliates having the largest probability of providing consolation. We discuss implications for the cross-species study of primate consolation and advocate that micro-sociology should reappraise ethological perspectives.
Introduction
“Man is a consolation-seeking creature,” the classical sociologist Georg Simmel (2010 [1918], p. 169) once proposed, while detailing that consolation “is something other than help—even an animal seeks help—but consolation is the remarkable experience that not only allows one to withstand suffering, but so to speak elevates suffering into suffering.” This aphorism attests to the fact that early sociology theorized on consolation and considered such empathetic behavior as something that sets humans apart from animals. As such, this view of consolation reminds us of how sociology has historically neglected the premise that “human beings are animals” (Collins, 1975, p. 153). From the perspective of a contemporary evolutionarily informed sociology (Freese, Li, & Wade, 2003; Turner, 2020), one should rather ask: To what extent consolation reflects our animal nature and thus supports the view that “the difference in mind between man and the higher animals, great as it is, certainly is one of degree and not of kind” (Darwin, 1871, p. 105).
In support of this similarity assertion, it is now well-established that non-human primates, and several other social animals, console distressed victims of aggression with hugs, kisses, and other forms of gentle touching (Pérez-Manrique & Gomila, 2018). This challenges the view—advocated by Simmel and maintained through the widespread rejection of biology within sociology (Massey, 2002)—that we, humans, because of our advanced cognitive capacities and culture, are uniquely capable of empathic emotions and comforting behaviors. However, empathic consolatory behavior should be understood as having a biological basis shared with our closest evolutionary kin. Leading primate ethologist, Frans de Waal (2006, p. 62), endorses this view and suggests that in evolutionary terms, it is parsimonious to assume that “if closely related species act the same, the underlying mental processes are probably the same, too.” Following this principle of evolutionary parsimony, it is suggested that several primate species, human and non-human alike, console conspecifics because of a shared capacity to empathically feel another's distress (de Waal & Preston, 2017). With limited attention devoted to the systematic study of human consolation, however, any empirical basis for a direct comparison of consolatory patterns between humans and other primates remains challenging.
Among the few human observational studies of consolation, the majority have been conducted on children (Verbeek, 2008). These developmental studies are pioneering but risk supporting the conjecture “that other primates are mentally like human children” (de Waal, 1989, p. 249, original italics). Although primate ethologists for decades have called for research on adult consolation (de Waal, 2000), the current literature offers but one quantitative observational study of consolation among human adults (Lindegaard et al., 2017 though see Bloch, Liebst, Poder, Christiansen, & Heinskou, 2018; Philpot & Levine, 2015 for qualitative assessments).
To address this gap, we investigate human adult consolation in the aftermath of real-life violent assaults in public spaces. To this end, we utilize techniques of naturalistic observation found within the often neglected ethological branch of micro-sociology—as pioneered by Erving Goffman (1971) with his vision for a field of ‘interaction ethology.’ Randall Collins, a former student of Goffman, is one of the few scholars that continues this tradition with the development of a micro-sociological theory that “relies heavily on methods of naturalistic observation found in ethology” (Collins & Sanderson, 2015, p. 276). This remains a fringe position, however, and the persistent absence of sociological consolation research thus encapsulates the striking point of John Levi Martin (2017, p. 118) that because ethological observation techniques have rarely been applied in sociology, “probably more is known about interactions between chimpanzees than interactions between humans.”
Besides its methodological importance, an interaction ethological approach may enhance micro-sociological theory with accounts of the biological processes involved in consolation and other interpersonal behaviors (Levi Martin, 2009). This is also appreciated by Collins (1975, p. 94) who suggests that “the basic variables that explain social interaction are provided by animal ethology.” According to de Waal (2008), the key variable underpinning consolation is an emotional contagion, or empathy, by which one individual is affected by another's distress. Importantly, de Waal's ethology is here aligned with Collins' micro-sociology, in particular with regards to their converging view that for humans, as well as in other animals, “social ties are fundamentally based on automatically aroused emotional responses” (Collins, 1975, p. 153). As we will elaborate upon in the next section, this empathy-based explanation is supported by evidence showing that consolation is predicted by social affiliation and female sex, two factors known to magnify empathic reactions (de Waal, 2008).
Prior research and hypotheses
In the current study, we test social affiliation and sex as predictors of human adult consolation. Positive associations between these factors and consolation would lend further support to an empathy account—while substantiating the shared view of ethology and ethologically informed micro-sociology that contagious emotional arousal is the basis of prosocial affiliative interaction. Thus, specifically, we test the two following hypotheses, both formulated a priori to data analysis: Bystanders who are socially affiliated with a physically harmed individual are more likely to provide consolation than socially unaffiliated bystanders (Hypothesis 1). Female bystanders are more likely to provide consolation to a physically harmed individual than male bystanders (Hypothesis 2).
Hypothesis 1 is formulated from evidence showing that amongst our closest evolutionary kin—bonobos and chimpanzees—consolation is preferentially provided to victims with whom bystanders are socially close, i.e., kin and affiliation partners (Clay & de Waal, 2013; Fraser, Stahl, & Aureli, 2008; Palagi & Norscia, 2011; Romero, Castellanos, & de Waal, 2010). Consistent with this pattern (though see Koski & Sterck, 2007), a video observational study by Lindegaard et al. (2017) found that social affiliation promoted consolation among human adults in the aftermath of commercial robberies. These results are in line with human behavioral evidence that affectionate touching is more common among individuals sharing relationship ties than among strangers (Suvilehto, Glerean, Dunbar, Hari, & Nummenmaa, 2015), and that group membership predicts bystander helping (Liebst et al., 2019; Phillips & Cooney, 2005; Slater et al., 2013) and a willingness to self-sacrifice for the group (Thye, Yoon, & Lawler, 2002; Swann Jr et al., 2014). More broadly, this expectation is consistent with an evolutionary account of cooperation, suggesting that help tends to be disproportionately provided between reciprocating individuals sharing social groups (de Waal, 2008).
A less settled debate is the significance of sex in the likelihood of providing consolation. While earlier studies on consolatory patterns in chimpanzee populations failed to establish an effect of sex (Fraser et al., 2008; de Waal, Aureli, & Russon, 1996), a more recent, larger-sampled study by Romero et al. (2010) found that consolation is more common among female than male chimpanzees. Lindegaard et al.’s (2017) human study also showed that women were more likely to provide consolation than men in post-conflict robberies. This cross-species evidence is consistent with psychobiological and evolutionary theory, which suggest that females, in general, are more empathic than males (Preston, 2013). Consequently, females exhibit a more prosocial ‘tend-and-befriend’ response to stress compared to the male-typical ‘fight-or-flight’ reaction (Taylor et al., 2000). While considering this based on nurture rather than nature, such sex difference is likewise predicted by social role theory (Eagly & Wood, 1999; Eagly, 2009), suggesting that women and men often differ in how they intervene in emergencies: Women tend to provide communal and relational support to others, while men tend to engage in a heroic or chivalrous fashion. In light of the above, we predict that women will provide disproportionately more consolation to victims than men (Hypothesis 2).
Besides social affiliation and sex, the paper considers the influence of a number of additional factors. First, this includes the number of individuals present at the emergency. The well-known ‘bystander effect’ suggests that the co-presence of others leads to a diffusion of responsibility and a lesser likelihood of emergency intervention (Darley & Latane, 1968). However, a recent meta-analysis of the bystander effect concludes that the dangerousness of an emergency may attenuate, or even reverse, this effect (Fischer et al., 2011). As such, the analysis accounts for bystander presence, although the literature is mixed with respect to the robustness and direction of the effect.
Second, early bystander research identified that cries of agony and visual cues of distress annul the ambiguity of whether bystander help is required (Solomon, Solomon, & Stone, 1978). This is in agreement with micro-sociological research suggesting that harmful victimization triggers sympathy and helping because of how it draws bystander attention to a single identifiable victim in need of help (Clark, 2007). Therefore, we include indicators of apparent victim injury as a control variable.
Third, contrary to what is often assumed, non-human primates do have a degree of culture, defined by socially learned behaviors (Sapolsky, 2006). However, arguably, one unique feature of human culture is its normative expectations of how one should behave (Tomasello, 2011). Intimate touching among humans is a highly culturally regulated form of interaction (Suvilehto et al., 2015), and this is likely to influence who, or who is not, expected to provide consolation. For example, studies show that service personnel strives to maintain an ‘emotional neutrality’ from those they interact with in an occupational capacity (Ward & McMurray, 2015). Therefore, we expect that bystanders in occupational roles (e.g., at bars, discotheques, convenience stores) are less likely to provide affectionate consolatory touching.
Fourth, social interaction is a continuous stream (Valach, Von Cranach, & Kalbermatten, 1988), but given our analytical interest in post-conflict behavior, we divide this stream into two time-frames—a conflict phase and a post-conflict phase. Because of this imposed separation, we account for whether the consolatory acts observed in the post-conflict are a ‘spillover’ of prior involvement in the conflict phase.
Finally, in addition to the hypothesized significance of social affiliation, the spatial proximity between the bystanders and the emergency conflict may also influence the likelihood of consolation. This is expected from the spatial principle that the level of social interaction between points in space tends to decay with increasing physical distance (Tobler, 1970). In line with this assumption, Clay and de Waal (2013) show that among bonobos, the probability of consolation increases with a bystander's proximity to the conflict. Contrastingly, Lindegaard et al. (2017) failed to find an effect of spatial proximity on consolation among human adults. We account for the effect of spatial proximity, even though the current state of evidence is mixed.
Method
Data
For the empirical analysis, we used video surveillance footage of real-life violent assaults recorded in urban public spaces (data, scripts, and materials are available at osf.io/qzfk3).1 Data were obtained from the Copenhagen Police Department, which provided access to 933 closed cases of violent assaults in the inner-city police districts of Copenhagen from 2010 to 2012. Of these, 164 contained video clips of varying quality and suitability for the present study. The video clips were accompanied by a written police case file containing descriptions of the event and the participants involved.
From the raw sample of videos, we selected clips that conformed to specific inclusion criteria: (1) Videos with sufficient technical quality to allow for detailed behavioral coding (e.g., high resolution and brightness). (2) Videos containing recordings of behavior in the post-conflict phase, after all violent acts had terminated. (3) Videos containing at least one victimized individual who could potentially be a recipient of consolation. (4) Videos capturing the duration of the post-conflict phase with none, or negligible, breaks in the interaction sequence (e.g., an individual or object temporally restricts the camera view) (see Nassauer & Legewie, 2018). In total, 49 video-recorded events were included in the study.
The majority of the included clips captured violent assaults occurring in night-time drinking settings (73% of videos), while the remaining incidents were recorded in daytime contexts (e.g., at shopping malls, on public transportation). The sample was heavily skewed towards incidents of male-on-male violence, with only three conflict situations involving female victims. This makes sense, since male-on-male conflicts are known to be particularly prevalent in night-time drinking settings (Graham & Wells, 2001). Given these factors, it seems reasonable to assume that most included incidents are cases of dispute-related violence rather than predatory violence (as exemplified by the robberies analyzed in Lindegaard et al., 2017; see also Felson, 1992).
Coding procedure
Four trained student assistants coded all video data using a study-specific behavioral codebook. This inventory was developed from prior bystander intervention and consolation study variables (Bloch et al., 2018; Levine, Taylor, & Best, 2011; Lindegaard et al., 2017; Philpot & Levine, 2015; de Waal & van Roosmalen, 1979) and from in-depth qualitative observations of a subsample of video clips (Jones, Jennings, Higgins, & De Waal, 2018).
Video coding began by identifying the point in time where the violent acts terminated and the post-conflict phase started. We then identified the individuals who had been physically harmed, as well as the bystanders who provided these victims with consolation. For the purpose of this study, a ‘bystander’ is any individual who is present at the post-conflict stage, thus potentially including earlier combatants. A bystander can be a consoling individual (e.g., gently touching a victim) or a non-consoling individual. All consoling bystanders were selected for coding. Next, we applied a case-control procedure to sample a control population from among the bystanders present who did not provide consolation (Grimes & Schulz, 2005). For videos capturing low-crowded settings (e.g., a convenience store with few customers), all non-consoling bystanders were selected as controls. For highly crowded settings (e.g., a packed dance floor), a subset of non-consoling bystanders was selected at random.
Individuals were only eligible for selection as non-consoling controls if at least minimally aware of the ongoing violent assault—put simply, without an awareness of the emergency event, an individual cannot be considered a bystander to that specific event. This assumption is in line with Goffman (1964) who defines a social situation as co-present individuals sharing mutual monitoring possibilities. Therefore, we assessed minimal awareness from the spatial closeness or visual accessibility to the event. For example, we assumed that individuals situated around the corner from a conflict could not be minimally aware and thus were not eligible for control selection.
Sampling more controls than positive cases—typically at a 1:4 ratio—is a means to improve statistical power (Grimes & Schulz, 2005). Our data have an approximate 1:7 ratio of cases to controls, which satisfies this criterion. In total, we selected 441 non-consoling bystanders as controls, which, combined with 60 cases of consoling bystanders, totaled an individual-level sample size of 501. Further, to ensure that the sampled controls were representative of the wider population of non-consoling bystanders for each context, we modeled data using sampling weights, scaled for multilevel models (Carle 2009).
We relied on the video material to code all variables of interest, with the exception of the social affiliation measurement (Hypothesis 1), where we triangulated footage with the corresponding police case files. Initially, coders were instructed to infer the existence of social relationships from nonverbal behavioral cues, described by Goffman (1971) as ‘tie-signs.’ These cues include interactional displays of collective behavior in concert, such as moving in synchrony, shared focus and attention, and bodily proximity (Liebst et al., 2023). In ambiguous cases, coders were instructed to validate their video-based social assessments against the police case descriptions. In the few cases where the data sources did not agree, the police files took precedence.
To test the reliability of the coded variables, we selected 25 video contexts, and 35 of individuals for double coding. As a rule of thumb, the threshold for acceptable interrater reliability is a Krippendorff's alpha value between 0.67 and 0.80 (De Swert, 2012; Krippendorff, 2004). All variables included in the analysis were close to, or surpassed, an alpha value of 0.80. Specifically, our dependent variable (consolation) and two hypothesized independent variables (social affiliation and sex) had alpha values of 0.94, 0.76, and 1.0, respectively.
Estimation
Our data have a hierarchical structure—with bystanders nested in emergency situations—that may violate the regression assumption of independence of observations. Multilevel modelling has been suggested as an appropriate estimation tool for nested data (Raudenbush & Sampson, 1999). We calculated the median odds ratio (MOR) to test the degree of between-cluster variation in our data (Merlo et al., 2006). The MOR of our intercept-only model was 1.8, which indicates that if bystanders are nested in emergencies with a high probability of consolation, their likelihood of providing consolation will (in median) increase approximately two-fold. This non-negligible degree of clustering confirms that a multilevel approach is appropriate.
Specifically, we applied a two-level multilevel logistic regression model with a random intercept. Estimation was performed with Stata 16's ‘melogit’ module. Note that a sufficient sample size is required to employ multilevel modeling. McNeish and Stapleton (2016) suggest that a minimum of 30 contexts, with an average of 5 individuals, typically yields unbiased fixed-effects point estimates. With an average of 10.2 individual-level observations across the 49 contexts, we comply with this recommendation.
Measures
Dependent variable. Consolation was captured with a binary measure where 1 = the bystander provides at least one consolatory act to a physically harmed individual across the post-conflict, and 0 = the bystander does not provide consolation. Based on studies from human and non-human primate research (Lindegaard et al., 2017; de Waal & van Roosmalen, 1979), we include hugging and gentle touching in the consolation measurement. Given that the function of consolation is to emotionally comfort a distressed other (de Waal, 2008), we excluded touching acts that served tangible or instrumental purposes (e.g., the victim's hand is touched when given a dropped item; or the physical touch involved in raising a victim from the ground).
In addition to physical expressions of consolation, our qualitative assessment of the video data suggested that consolation may also be provided in non-physical forms: The consoler enters the victim's intimate sphere (i.e., one arm's length) and is fully attentive to the victim for at least 10 s. This non-physical consolatory display is supported by behavioral evidence suggesting that proximity and attentiveness are typical ways by which humans comfort each other (Bullis & Horn, 1995). Furthermore, in the non-human primate literature, consolation is described as involving non-physical aspects of visual inspection of the recipient's injuries (Clay & de Waal, 2013).
Descriptive statistics (N = 501, unweighted)
| M | freq. | SD | Min | Max | |
| Consolation | |||||
| No | 0.88 | 441 | 0 | 1 | |
| Yes | 0.12 | 60 | 0 | 1 | |
| Social affiliation | |||||
| No | 0.86 | 432 | 0 | 1 | |
| Yes | 0.14 | 69 | 0 | 1 | |
| Sex | |||||
| Male | 0.73 | 368 | 0 | 1 | |
| Female | 0.27 | 133 | 0 | 1 | |
| Prior involvement | |||||
| No | 0.79 | 395 | |||
| Yes | 0.21 | 106 | |||
| Number of bystanders | 16.53 | 13.23 | 1 | 69 | |
| Number of bystanders (standardized) | 0.05 | 0.48 | −0.50 | 1.94 | |
| Apparent victim injuries | |||||
| No | 0.17 | 85 | 0 | 1 | |
| Yes | 0.83 | 416 | 0 | 1 | |
| Bystander at work | |||||
| No | 0.90 | 451 | 0 | 1 | |
| Yes | 0.10 | 50 | 0 | 1 | |
| Spatial proximity | |||||
| No | 0.64 | 323 | 0 | 1 | |
| Yes | 0.36 | 178 | 0 | 1 | |
Independent variables. Social affiliation was measured with a binary variable where 1 = the bystander has a social relationship with one or more physically harmed victims, and 0 = the bystander has no social relationship with any victim. Sex was captured with a binary variable where 1 = female and 0 = male, determined through a visual evaluation.
Control variables. Prior involvement represents whether the individual was involved in the conflict phase of the emergency, either as an antagonist or as a bystander performing escalatory or de-escalatory actions. This is a binary variable where 1 = the individual was involved in the prior conflict, and 0 = the individual was not involved. Number of bystanders is a continuous context-level variable operationalizing the (possibly reversed) bystander effect. This variable records the number of individuals present in the post-conflict phase, standardized by subtracting the mean and dividing by two standard deviations as to make it comparable to binary predictor effect sizes (Gelman, 2008). Apparent injuries is included as an indicator of situational ambiguity and is captured with a binary context-level variable where 1 = one or more victims in the emergency have visually apparent injures (i.e., low ambiguity), and 0 = no victims have apparent injuries. Spatial proximity is a binary variable where 1 = the bystander is within a 2-m radius from where the conflict initiates, and 0 = the bystander is more than 2 m away from this epicenter. Bystander at work is a binary variable where 1 = the bystander is performing an occupational role (e.g., as a bouncer, bar staff), and 0 = the bystander is not at work.
Ethics
Approval of the study was obtained from the Danish Data Protection Agency through the joint notification of the Faculty of Social Sciences at the University of Copenhagen (J. No.: 2015-57-0125-0026). Further, the study complies with the American Psychological Association's (2017) ethical principles, most importantly § 8.03, stating that researchers may dispense from obtaining informed consent from video-recorded participants if the research—as in the current case—consists of naturalistic observations in public places.
Results
Descriptively, we found that the consoling and non-consoling bystanders are unequally distributed across the sampled video contexts, with 49% of the videos containing at least one consoling bystander. On average, there were 1.2 consolers per situation. Figure 1 presents the results of our confirmatory regression analysis. There was a statistically significant association between social affiliation and the consolation outcome (OR = 7.41, 95% CI [1.91, 28.78], p = 0.004). The odds ratio estimate suggested that a bystander who was socially affiliated with a victim was approximately seven times more likely to provide consolation than an unrelated bystander. This is a large effect size (Rosenthal, 1996), although the length of the confidence interval suggested that the degree of influence of social affiliation on consolation could range from a small-medium to a very large effect size. Expressed as predicted probabilities, with other variables held constant at their means, the consolation provision likelihood of socially affiliated bystanders was 0.26, while the corresponding likelihood for strangers was 0.05. Taken together, this result provided compelling evidence for the hypothesized influence of social affiliation on consolation (Hypothesis 1).
Multilevel regression of consolation
Citation: Culture and Evolution 20, 1; 10.1556/2055.2023.00018
There was no statistically significant association between sex and the consolation outcome (OR = 1.28, 95% CI [0.56, 2.93], p = 0.57). This failed to confirm the expectation that women would provide disproportionately more consolation than men (Hypothesis 2). The statistically significant and non-significant results regarding social affiliation and sex, respectively, showed very strong stability across other possible model specifications (see Young, 2018).
In a further explorative analysis, we assessed whether sex was associated with consolation in an interaction effect with social affiliation. This was estimated using a linear probability rather than a logistic model, given that a logistic approach had convergence issues and, in general, offers a less straightforward manner to compute interaction effects than linear estimation (Breen, Karlson, & Holm, 2018). The interaction effect between social affiliation and sex was statistically significant (β = 0.36, 95% CI [0.08, 0.64], p = 0.012). This result is illustrated in Fig. 2, showing that the average effect of social affiliation—with affiliated persons being more likely to console than strangers—was larger for women than for men. Given that exploratory assessments of interaction effects are a possible source of false positives (Wicherts et al., 2016), we also examined the robustness of the social affiliation-sex interaction across other possible model specifications. With a marginally significant average p-value of 0.03 and 83% significant results across 512 alternative model specifications, the interaction effect demonstrated a moderate level of robustness.2
Probability of consolation by sex and social affiliation
Note. Error bars represent 95% confidence intervals. The relatively broad confident intervals indicate that we are reaching the limit for how much data may be subdivided; there are relatively few women and affiliated in the sample (see Table 1) and only, in sum, 12 affiliated women.
Citation: Culture and Evolution 20, 1; 10.1556/2055.2023.00018
Finally, a number of the included control variables were associated with the consolation outcome (see Fig. 1). The number of bystanders showed a negative association with consolation. Further, as expected, the estimation suggested that the presence of a victim with apparent injuries was a very strong positive predictor of consolation. Also, in line with expectations, we found that the control variable measuring whether the bystander is performing an occupational role was negatively associated with consolation. The individual's prior involvement and spatial proximity to the conflict showed no significant associations with the consolation outcome.
Discussion
In comparison to the non-human primate literature, the provision of human consolation, especially among adults, has received limited attention. To address this research gap, we tested the predictive power of social affiliation and sex on the likelihood of consolatory intervention using CCTV-captured public assaults. Our data provided compelling support for the prediction that social affiliation promotes consolation (Hypothesis 1). By comparison, we found no support for a main effect of sex on the likelihood of providing consolation (Hypothesis 2). However, a subsequent exploratory analysis found moderately robust evidence that group affiliation positively predicted the likelihood of intervention for both sexes, yet strongest in magnitude for female affiliates.
Our finding that social affiliation promotes bystander involvement is consistent with sociological work describing how relationship ties increase the likelihood of third-party action during physical disputes (Liebst et al., 2019; Phillips & Cooney, 2005). Further, our results are in line with a comprehensive body of non-human primate research (Palagi & Norscia, 2011; e.g., Romero et al., 2010), as well as the only existing quantitative study of human-adult consolation (Lindegaard et al., 2017), showing that social affiliation predicts consolatory behavior specifically. Thus, the influence of social affiliation on consolation appears to be generalizable across different types of violent emergencies, spanning from predatory victimizations in commercial robberies (as analyzed in Lindegaard et al., 2017) to our current cases, which predominantly include male-on-male dispute-related violence in night-time drinking settings.
A common explanatory thread throughout the consolation literature is that social group ties promote feelings of empathy between associated individuals, which in turn motivate the comforting of distressed peers. This underpinning empathy mechanism, detailed within ethology (de Waal & Preston, 2017), extends beyond the provision of consolation to a broader range of helping and supporting behaviors. For example, it is well established that individuals feel more empathic towards in-group members than out-group members (Vanman, 2016), and that this socially magnified empathy may positively mediate helping intentions and actions (Stürmer, Snyder, Kropp, & Siem, 2006). Although not established through a direct empathy measurement, the current finding that social affiliation predicts consolation is in line with the interpretation that bystander helping is shaped by empathic emotions.
Even though we did not find the hypothesized sex difference in the provision of consolation, similar non-associations are reported within the consolation literature. In non-human primate research, earlier studies failed to find a sex difference in consolation (de Waal et al., 1996; Fraser et al., 2008). More recently, Romero et al. (2010) reported that females console disproportionately more than males—however, this difference held only for female individuals of low and medium rank. Moreover, in Lindegaard et al.’s (2017) human adult study, the observed effect size of sex (OR = 2.72), although significant, was substantially smaller than the estimated effect of social affiliation (OR = 7.69).
These mixed findings exemplify current perspectives on sex and helping, which stress that the similarities between women and men are often overlapping and as important as the differences (Hyde, 2014). In this perspective, when sex differences in prosocial helping are found, these should be ascribed to role expectations—more so than psychobiological propensities. Adding to this, gendered role expectations shape prosocial behavior in conjunction with other social roles, especially in family and friend relationships, where women tend to provide more caring support than men (Eagly, 2009). These predictions are in line with the interaction effect found in the current study, which indicates that it is victim-affiliated women who are most likely to provide consolatory help. Thus, compared to Lindegaard et al. (2017), who found a significant main effect of sex and, therefore, ascribed this mainly to psychobiological sex differences, we here propose that it is the intersection between gender and social friendship roles that underpin the currently observed difference in helping.
We identified a number of control variables associated with consolation. First, in line with the bystander effect hypothesis (Darley & Latane, 1968), we found that consolation is negatively associated with the number of bystanders. As such, our result runs counter to recent evidence suggesting that the bystander effect reverses in dangerous emergencies (Fischer et al., 2011; Lindegaard et al., 2017). However, given that the consolation recorded in our study occurs post-conflict—after the violence has ceased—the danger condition assumed to reverse the bystander effect may not be present. Further, it should be stressed that the current result cannot settle the discussion of whether the negative impact of bystander presence reflects bystander apathy (Darley & Latane, 1968), or rather a helping saturation in which there are more potential help-givers than required (Liebst et al., 2019).
Second, in support of the expectation that visual cues of distress facilitate bystander intervention (Solomon et al., 1978), we found that victims with apparent injuries were disproportionately more likely to be consoled. Victim injuries may signal to bystanders that a consoling response is required (Bloch et al., 2018; Clark, 2007). More broadly, the association between visual cues of victimization and helping behavior is consistent with Turner's (2010) micro-sociological argument that in humans and other primates, the visual sense is dominant and thus the basis for emotional communication.
Third, we found that bystanders performing an occupational role were less likely to console victims than members of the public. This result supports studies suggesting that employees in public maintain emotional neutrality from the public whom they serve (Ward & McMurray, 2015). Fourth, we found no evidence that consolation behavior is a spillover effect of prior conflict involvement. This resembles Black's (1993) argument that conflict ‘healers’ should be defined by how they manage the implications of a conflict without necessary involvement in the preceding conflict itself.
Finally, consistent with Lindegaard et al.’s (2017) findings from human robbery data—but contrary to Clay and de Waal's (2013) study on consolation among bonobo apes—we found that the bystanders' spatial proximity to the conflict does not predict consolation. This suggests that the provision of human bystander consolation is not shaped by physical distance per se. More broadly, this finding links to the observation that human interaction—because of its highly symbolic (Collins, 1975), identity-based (Levine & Thompson, 2004), object-mediated nature (Latour, 1996)—is less dependent on mere physical co-presence than the interactions of non-human primates.
Study limitations
Several limitations of the current study should be considered. First, a known drawback of surveillance camera footage is that sound and verbal communications are not typically recorded (Philpot, Liebst, Møller, Lindegaard, & Levine, 2019). While this omission undoubtedly provides an incomplete picture of the full social interaction under study, this exclusion should not be overstated—a substantial share of human communication is known to be expressed in non-verbal form (Burgoon, Guerrero, & Manusov, 2011). Further, the meaning of certain verbal expressions has nonverbal behavioral equivalents (Eibl-Eibesfeldt, 1989) and can thus be partially inferred without sound (e.g., threatening verbal accusations and aggressive body gestures are typically expressed in unison). In addition, scholars can triangulate visual data with other data sources providing information on verbal exchanges, as in the current study that utilized police case files to access self-reported accounts.
A second and important issue concerns the fact that our video data are not a random sample but is restricted to police-reported events that tend to involve more serious violence than unreported incidents (Lindegaard & Bernasco, 2018). Given our finding that apparent victim injury is associated with consolatory helping, it is plausible that consolation is overrepresented in our police-reported sample. Therefore, we should be wary of generalizing our results to less severe contexts that remain unreported to the police. Further, given the sample's skewness towards assaults in public drinking areas, the current study may have generalizability issues related to alcohol intoxication, which may have affected bystander judgments and thus the reported findings. As suggested by Philpot et al. (2019), where possible, future research should prioritize probability sampling of incidents.
Finally, similar to existing observational studies (Lindegaard et al., 2017; e.g., Romero et al., 2010), we assume that consolation is motivated by empathy and fulfills a comforting function rather than relying on direct (e.g., self-reported) measurements of these psychological aspects. The challenge is that the alternative—to define consolation without an eye for its psychological content—risks undermining the content validity of this behavioral measurement. Human action manifests itself in physical movement, but as Valach et al. (Valach et al., 1988, p. 255) stress, psychological meaning is key to segmenting “the stream of behavior into meaningful units on the level of acts.” For example, we followed this recommendation when extending the definition of consolation to include non-physical displays. Specifically, both our qualitative assessment of the data and studies of comforting strategies (Bullis & Horn, 1995), suggested that the goal-directed meaning of proximity and attention is victim-consoling. Given that such interpretation can impute erroneous meaning-content to the behavior under study, however, future research should seek to verify and include direct measurements of the empathic and comforting underpinnings of consolation.
Implications for micro-sociology
In this study, we applied a synthesis of micro-sociology and ethology as a method to systematically examine how real-life helping encounters unfold. This interaction ethological approach was pioneered by Goffman (1971), but has rarely been practiced since (key exceptions include Collins, 1975; Kendon, 1990; Levi Martin, 2009, and more broadly the subfield of human ethology; Eibl-Eibesfeldt, 1989; Richer, Hendrie, Oberzaucher, Fisher, & Segal, 2017). From the experiences gained through the application of this method, we offer some ideas that may guide and encourage future helping research within this underappreciated ethological branch of micro-sociology. An interaction ethological approach broadens the epistemological toolbox of micro-sociology to consider both ‘proximate’ (i.e., psychophysiological) and ‘ultimate’ (i.e., evolutionary adaptive) causes of consolation behavior (Tinbergen, 1963)—an explanatory distinction that, among others, Freese et al. (2003) have encouraged sociologists to embrace.
In terms of proximate causation, our discussion of the psychological mechanisms underpinning consolation across primate species re-actualizes Collins' (1975) argument that animal ethology provides micro-sociology with some of the basic variables explaining social interaction. Specifically, it is plausible that humans and non-human primates share a neurological capacity for emotional contagion (Collins, 2004; Heinskou & Liebst, 2016; Turner & Maryanski, 2012)—a capacity that facilitates similar expressions of consolatory displays across these evolutionarily related species (de Waal & Preston, 2017). As mentioned, this assertion is in line with our result that affiliation, a known correlate of empathic emotions, is positively associated with consolation.
Both Goffman (1971) and Collins (1975) have expressed concerns about applying a simplified Darwinian framework to explain all social phenomena in terms of ultimate causes of evolutionary survival value (though see Kelly & Archibald, 2019). However, since the 1970s, research in ethology and the biological sciences have taken a ‘social turn’ that pinpoints how biological and social processes are intertwined, as well as how cooperative and prosocial behaviors operate within evolution (Meloni, 2014). Given these developments, it is sensible also for sociologists to evaluate an empathy account of consolation in evolutionary terms. The argument that social affiliation facilitates empathy and helping behavior is consistent with an evolutionary theory of cooperation that would expect prosocial reactions between reciprocating or genetically related individuals who share interdependent ties (de Waal, 2008).
In our consolation data, the absence of a main effect of sex, as well as the presence of an interaction between sex and social affiliation, is also meaningful from the evolutionary perspective that human beings are more biologically adapted to cultural transmission and accumulation and hence behavioral variability, than other primates (Boyd & Silk, 2014; Turner, 2020). As Eibl-Eibesfeldt (1989, p. 15), the pioneering scholar of human ethology states: “With cultural evolution, mankind developed an adaptive mechanism that in historical times has no doubt exceeded the biological ones in importance.” This co-evolution of biology and culture in humans is likely to allow for social variation in how each sex, shaped by gender role expectations, provides help to others (Eagly, 2009). At the same time, we must acknowledge criticisms highlighting that this interpretation risks overlooking how evolved dispositions contribute to both behavioral and psychological differences between men and women (Stewart-Williams & Thomas, 2013).
In terms of methodological contributions, ethology offers micro-sociology an important reminder of the scientific value of systematic behavioral observation (Reiss Jr, 1992; Richer et al., 2017). The timing has never been more pertinent, given the ‘observational revolution’ (Dawkins, 2007, p. 139) taking place within ethology from the advancement of video technologies. This opportunity has not been overlooked by sociologists who identify that a “video revolution has made available much more information about what happens in violent situations than ever before” (Collins, 2008, p. 5). This assertion is now evident, given the rapid growth of video-based assessments providing fresh and fine-grained insights into the escalatory and consolatory behaviors in human conflict encounters (Lindegaard & Bernasco, 2018; Nassauer & Legewie, 2018). Stressing this point, the current study could simply not have been reliably conducted with self-reported data (e.g., interviews, surveys), which is the default methodology of most sociological research (Jerolmack & Khan, 2014).
Micro-sociology is often defined as interpretative epistemology, as opposed to a quantitative observational study of social life. For example, this view is reflected in Blumer's (1969) influential ‘variable sociology’ critique that quantification decontextualizes social life from the meaningful here-and-now. However, we believe that our and others' (Levi Martin, 2009) advancements toward an ethologically informed micro-sociology have addressed the key points of Blumer's once-justified critique. In our case, the interaction ethological method led us to conduct our quantifications through video-assisted naturalistic observations of consolatory encounters as they unfold in their here-and-now contexts. Further, we applied a multilevel tool that allowed us to estimate bystander behavior as nested in, rather than abstracted away from, their situational ecology (see also Raudenbush & Sampson, 1999). These methodological steps satisfy, at least in part, Blumer's (1969, p. 152) context-sensitive ideal of a naturalistic inquiry that has “the virtue of remaining in close and continuing relations with the natural social world.” Further, with respect to the meaningfulness of social action, we recognized in the data coding process that bystander consolation behaviors carry psychological meaning, and these actions should be measured with an interpretative sensitivity to this fact (e.g., our qualitative pre-analysis led us to include non-physical comforting strategies).
Taken together, rather than treating the Blumerian criticism as something that pits micro-sociology against behavioral quantification, the ambition should be to incorporate these criticisms into the reemerging foundation of a quantitatively informed interaction ethology. We consider this study as a stone in this foundation and hope that it may serve as a basis for future micro-sociological studies on human consolation and other behaviors.
Acknowledgment
This work was supported by the Danish Council for Independent Research (DFF-6109-00210) and the Velux Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or manuscript preparation.
References
American Psychological Association (2017). Ethical principles of psychologists and code of conduct. Washington DC: American Psychological Association.
Black, D. (1993). The social structure of right and wrong. Academic Press.
Bloch, C., Liebst, L. S., Poder, P., Christiansen, J. M., & Heinskou, M. B. (2018). Caring collectives and other forms of bystander helping behavior in violent situations. Current Sociology, 66(7), 1049–1069. https://doi.org/10.1177/0011392118776365.
Blumer, H. (1969). Symbolic interaction: perspective and method. Prentice-Hall.
Boyd, R., & Silk, J. B. (2014). How humans evolved. WW Norton & Company.
Breen, R., Karlson, K. B., & Holm, A. (2018). Interpreting and understanding logits, probits, and other nonlinear probability models. Annual Review of Sociology, 44(1), 39–54. https://doi.org/10.1146/annurev-soc-073117-041429.
Bullis, C., & Horn, C. (1995). Get a little closer: Further examination of nonverbal comforting strategies. Communication Reports, 8(1), 10–17. https://doi.org/10.1080/08934219509367602.
Burgoon, J. K., Guerrero, L. K., & Manusov, V. (2011). Nonverbal signals. In M. L. D. Knapp, & J. A. Daly (Eds.), The SAGE handbook of interpersonal communication. Sage.
Clark, C. (2007). Misery and company: sympathy in everyday life. University of Chicago Press.
Clay, Z., & de Waal, F. B. M. (2013). Bonobos respond to distress in others: Consolation across the age spectrum. Plos One, 8(1), e55206. https://doi.org/10.1371/journal.pone.0055206.
Collins, R. (1975). Conflict sociology: toward an explanatory science. Academic Press.
Collins, R. (2004). Interaction ritual chains. Princeton University Press.
Collins, R. (2008). Violence: a micro-sociological theory. Princeton University Press.
Collins, R., & Sanderson, S. K. (2015). Conflict sociology: a sociological classic updated. Routledge.
Darley, J. M., & Latane, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 8(4, Pt.1), 377–383. https://doi.org/10.1037/h0025589.
Darwin, C. (1871). The descent of man, and selection in relation to sex. John Murray.
Dawkins, M. S. (2007). Observing animal behaviour: design and analysis of quantitative data. Oxford University Press.
De Swert, K. (2012). Calculating inter-coder reliability in media content analysis using Krippendorff’s Alpha. University of Amsterdam, Center for Politics and Communication. University of Amsterdam. https://www.polcomm.org/wp-content/uploads/ICR01022012.pdf.
Eagly, A. H. (2009). The his and hers of prosocial behavior: An examination of the social psychology of gender. American Psychologist, 64(8), 644. https://doi.org/10.1037/0003-066X.64.8.644.
Eagly, A. H., & Wood, W. (1999). The origins of sex differences in human behavior: Evolved dispositions versus social roles. American Psychologist, 54, 408–423. https://doi.org/10.1037/0003-066X.54.6.408.
Eibl-Eibesfeldt, I. (1989). Human ethology. Aldine de Gruyter.
Felson, R. (1992). Predatory and dispute-related violence: A social interactionist approach. In R. Clarke, & M. Felson (Eds.), Routine activities and rational choice: advances in criminological theory (pp. 103–125). Transaction Publishers.
Fischer, P., Krueger, J. I., Greitemeyer, T., Vogrincic, C., Kastenmüller, A., Frey, D., … Kainbacher, M. (2011). The bystander-effect: A meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. Psychological Bulletin, 137(4), 517–537. https://doi.org/10.1037/a0023304.
Fraser, O. N., Stahl, D., & Aureli, F. (2008). Stress reduction through consolation in chimpanzees. Proceedings of the National Academy of Sciences, 105(25), 8557–8562. https://doi.org/10.1073/pnas.0804141105.
Freese, J., Li, J.-C. A., & Wade, L. D. (2003). The potential relevances of biology to social inquiry. Annual Review of Sociology, 29(1), 233–256. https://doi.org/10.1146/annurev.soc.29.010202.100012.
Gelman, A. (2008). Scaling regression inputs by dividing by two standard deviations. Statistics in Medicine, 27(15), 2865–2873. https://doi.org/10.1002/sim.3107.
Goffman, E. (1964). The neglected situation. American Anthropologist, 66(6_PART2), 133–136. https://doi.org/10.1525/aa.1964.66.suppl_3.02a00090.
Goffman, E. (1971). Relations in public. Microstudies of public order. Basic Books.
Graham, K., & Wells, S. (2001). The two worlds of aggression for men and women. Sex Roles, 45, 595–622.
Grimes, D. A., & Schulz, K. F. (2005). Compared to what? Finding controls for case-control studies. Lancet, 365(9468), 1429–1433. https://doi.org/10.1016/S0140-6736(05)66379-9.
Heinskou, M. B., & Liebst, L. S. (2016). On the elementary neural forms of micro-interactional rituals: Integrating autonomic nervous system functioning into interaction ritual theory. Sociological Forum, 31(2), 354–376. https://doi.org/10.1111/socf.12248.
Hyde, J. S. (2014). Gender similarities and differences. Annual Review of Psychology, 65, 373–398. https://doi.org/10.1146/annurev-psych-010213-115057.
Jerolmack, C., & Khan, S. (2014). Talk is cheap: Ethnography and the attitudinal fallacy. Sociological Methods & Research, 43(2), 178–209. https://doi.org/10.1177/0049124114523396.
Jones, L. K., Jennings, B. M., Higgins, M. K., & De Waal, F. B. M. (2018). Ethological observations of social behavior in the operating room. Proceedings of the National Academy of Sciences, 115(29), 7575–7580. https://doi.org/10.1073/pnas.1716883115.
Kelly, B. W., & Archibald, W. P. (2019). Erving goffman and the evolutionary ecological missing link. The Interaction Order. Studies in Symbolic Interaction, 50, 141–168. https://doi.org/10.1108/S0163-239620190000050007.
Kendon, A. (1990). Conducting interaction: patterns of behavior in focused encounters (Vol. 7). CUP Archive.
Koski, S. E., & Sterck, E. H. (2007). Triadic postconflict affiliation in captive chimpanzees: Does consolation console? Animal Behaviour, 73(1), 133–142. https://doi.org/10.1016/j.anbehav.2006.04.009.
Krippendorff, K. (2004). Reliability in content AnalysisSome common misconceptions and recommendations. Human Communication Research, 30(3), 411–433. https://doi.org/10.1111/j.1468-2958.2004.tb00738.x.
Latour, B. (1996). On interobjectivity. Mind, Culture, and Activity, 3(4), 228–245. https://doi.org/10.1207/s15327884mca0304_2.
Levi Martin, J. (2009). Formation and stabilization of vertical hierarchies among adolescents: Towards a quantitative ethology of dominance among humans. Social Psychology Quarterly, 72(3), 241–264. https://doi.org/10.1177/019027250907200307.
Levine, M., Taylor, P. J., & Best, R. (2011). Third parties, violence, and conflict resolution: The role of group size and collective action in the microregulation of violence. Psychological Science, 22(3), 406–412. https://doi.org/10.1177/0956797611398495.
Levine, M., & Thompson, K. (2004). Identity, place, and bystander intervention: Social categories and helping after natural disasters. The Journal of Social Psychology, 144(3), 229–245. https://doi.org/10.3200/SOCP.144.3.229-245.
Liebst, L. S., Baggesen, L., Dausel, K. L., Pallante, V., & Lindegaard, M. R. (2023). Human observers are accurate in judging personal relationships in real-life settings: A methodological tool for human observational research. Field Methods, 35(4), 364–377. https://doi.org/10.1177/1525822X231158888.
Liebst, L. S., Heinskou, M. B., & Ejbye-Ernst, P. (2018). On the actual risk of bystander intervention: A statistical study based on naturally occurring violent emergencies. Journal of Research in Crime and Delinquency, 55(1), 27–50.
Liebst, L. S., Philpot, R., Bernasco, W., Dausel, K. L., Ejbye‐Ernst, P., Nicolaisen, M. H., & Lindegaard, M. R. (2019). Social relations and presence of others predict bystander intervention: Evidence from violent incidents captured on CCTV. Aggressive Behavior, 45(6), 598–609. https://doi.org/10.1002/ab.21853.
Lindegaard, M. R., & Bernasco, W. (2018). Lessons learned from crime caught on camera. Journal of Research in Crime and Delinquency, 55(1), 155–186. https://doi.org/10.1177/0022427817727830.
Lindegaard, M. R., Liebst, L. S., Bernasco, W., Heinskou, M. B., Philpot, R., Levine, M., & Verbeek, P. (2017). Consolation in the aftermath of robberies resembles post-aggression consolation in chimpanzees. Plos One, 12(5). https://doi.org/10.1371/journal.pone.0177725.
Martin, J. L. (2017). Thinking through methods: a social science primer. University of Chicago Press.
Massey, D. S. (2002). A brief history of human society: The origin and role of emotion in social life. American Sociological Review, 67(1), 1–29. https://doi.org/10.2307/3088931.
McNeish, D. M., & Stapleton, L. M. (2016). The effect of small sample size on two-level model estimates: A review and illustration. Educational Psychology Review, 28(2), 295–314. https://doi.org/10.1007/s10648-014-9287-x.
Meloni, M. (2014). How biology became social, and what it means for social theory. The Sociological Review, 62(3), 593–614. https://doi.org/10.1111/1467-954X.12151.
Merlo, J., Chaix, B., Ohlsson, H., Beckman, A., Johnell, K., Hjerpe, P., … Larsen, K. (2006). A brief conceptual tutorial of multilevel analysis in social epidemiology: Using measures of clustering in multilevel logistic regression to investigate contextual phenomena. Journal of Epidemiology and Community Health, 60(4), 290–297. https://doi.org/10.1136/jech.2004.029454.
Nassauer, A., & Legewie, N. M. (2018). Video data analysis: A methodological frame for a novel research trend. Sociological Methods & Research. https://doi.org/10.1177/0049124118769093.
Olvera Astivia, O. L., Gadermann, A., & Guhn, M. (2019). The relationship between statistical power and predictor distribution in multilevel logistic regression: A simulation-based approach. BMC Medical Research Methodology, 19, 1–20. https://doi.org/10.1186/s12874-019-0742-8.
Palagi, E., & Norscia, I. (2011). Scratching around stress: Hierarchy and reconciliation make the difference in wild brown lemurs (Eulemur fulvus). Stress, 14(1), 93–97. https://doi.org/10.3109/10253890.2010.505272.
Pérez-Manrique, A., & Gomila, A. (2018). The comparative study of empathy: Sympathetic concern and empathic perspective-taking in non-human animals. Biological Reviews of the Cambridge Philosophical Society, 93(1), 248–269. https://doi.org/10.1111/brv.12342.
Phillips, S., & Cooney, M. (2005). Aiding peace, abetting violence: Third parties and the management of conflict. American Sociological Review, 70(2), 334–354. https://doi.org/10.1177/000312240507000207.
Philpot, R., & Levine, M. (2015). Tackling violent crime in public spaces: Lessons from a CCTV micro-analysis. Paper presented at the Presentation given at the at the Annual Meeting of the European Society of Criminology (Eurocrim).
Philpot, R., Liebst, L. S., Møller, K. K., Lindegaard, M. R., & Levine, M. (2019). Capturing violence in the night-time economy: A review of established and emerging methodologies. Aggression and Violent Behavior, 46, 56–65. https://doi.org/10.1016/j.avb.2019.02.004.
Preston, S. D. (2013). The origins of altruism in offspring care. Psychological Bulletin, 139, 1305–1341. https://doi.org/10.1037/a0031755.
Raudenbush, S. W., & Sampson, R. J. (1999). Ecometrics: Toward a science of assessing ecological settings, with application to the systematic social observation of neighborhoods. Sociological Methodology, 29(1), 1–41. https://doi.org/10.1111/0081-1750.00059.
Reiss, A. J., Jr (1992). The trained incapacities of sociologists. In T. Halliday, & M. Janowitz (Eds.), Sociology and its publics (pp. 297–315). University of Chicago Press Chicago.
Richer, J., Hendrie, C., Oberzaucher, E., Fisher, M., & Segal, N. (2017). Direct observation of human behaviour what it is and why it must be done. Human Ethology Bulletin, 32, 3–5. https://doi.org/10.22330/heb/324/003-005.
Romero, T., Castellanos, M. A., & de Waal, F. B. M. (2010). Consolation as possible expression of sympathetic concern among chimpanzees. Proceedings of the National Academy of Sciences, 107(27), 12110–12115. https://doi.org/10.1073/pnas.1006991107.
Rosenthal, J. A. (1996). Qualitative descriptors of strength of association and effect size. Journal of Social Service Research, 21(4), 37–59. https://doi.org/10.1300/J079v21n04_02.
Sapolsky, R. M. (2006). Culture in animals: The case of a non-human primate culture of low aggression and high affiliation. Social Forces, 85(1), 217–233. https://doi.org/10.1353/sof.2006.0142.
Simmel, G. (2010). The view of life: four metaphysical essays with journal aphorisms. University of Chicago Press.
Slater, M., Rovira, A., Southern, R., Swapp, D., Zhang, J. J., Campbell, C., & Levine, M. (2013). Bystander responses to a violent incident in an immersive virtual environment. Plos One, 8(1), e52766. https://doi.org/10.1371/journal.pone.0052766.
Solomon, L. Z., Solomon, H., & Stone, R. (1978). Helping as a function of number of bystanders and ambiguity of emergency. Personality & Social Psychology Bulletin, 4(2), 318–321. https://doi.org/10.1177/014616727800400231.
Stewart-Williams, S., & Thomas, A. G. (2013). The ape that thought it was a peacock: Does evolutionary psychology exaggerate human sex differences? Psychological Inquiry, 24, 137–168.
Stürmer, S., Snyder, M., Kropp, A., & Siem, B. (2006). Empathy-motivated helping: The moderating role of group membership. Personality & Social Psychology Bulletin, 32(7), 943–956. https://doi.org/10.1177/0146167206287363.
Suvilehto, J. T., Glerean, E., Dunbar, R. I. M., Hari, R., & Nummenmaa, L. (2015). Topography of social touching depends on emotional bonds between humans. Proceedings of the National Academy of Sciences of the United States of America, 112(45), 13811–13816. https://doi.org/10.1073/pnas.1519231112.
Swann, W. B., Jr, Buhrmester, M. D., Gómez, A., Jetten, J., Bastian, B., Vázquez, A., … Cui, L. (2014). What makes a group worth dying for? Identity fusion fosters perception of familial ties, promoting self-sacrifice. Journal of Personality and Social Psychology, 106(6), 912. https://doi.org/10.1037/a0036089.
Taylor, S. E., Klein, L. C., Lewis, B. P., Gruenewald, T. L., Gurung, R. A., & Updegraff, J. A. (2000). Biobehavioral responses to stress in females: Tend-and-befriend, not fight-or-flight. Psychological Review, 107(3), 411–429. https://doi.org/10.1037/0033-295x.107.3.411.
Thye, S. R., Yoon, J., & Lawler, E. J. (2002). The theory of relational cohesion: Review of a research program research program. Advances in group processes (pp. 139–166). Emerald Group Publishing Limited. https://doi.org/10.1016/S0882-6145(02)19006-0.
Tinbergen, N. (1963). On aims and methods of ethology. Zeitschrift Für Tierpsychologie, 20(4), 410–433. https://doi.org/10.1111/j.1439-0310.1963.tb01161.x.
Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240. https://doi.org/10.2307/143141.
Tomasello, M. (2011). Human culture in evolutionary perspective. In M. J. Gelfand, C.-y Chiu, & Y.-y Hong (Eds.), Advances in culture and psychology (Vol. 1, pp. 5–51). Oxford University Press.
Turner, J. H. (2010). Theoretical principles of sociology (Vol. 2). Microdynamics: Springer.
Turner, J. H. (2020). On human nature. The biology and sociology of what made us human. Routledge. https://doi.org/10.4324/9781003094500.
Turner, J. H., & Maryanski, A. (2012). The biology and neurology of group processes. In W. Kalkhoff, S. R. Thye, & E. J. Lawler (Eds.), Biosociology and neurosociology (Vol. 29, pp. 1–37). Emerald Group Publishing Limited. https://doi.org/10.1108/S0882-6145(2012)0000029004.
Valach, L., Von Cranach, M., & Kalbermatten, U. (1988). Social meaning in the observation of goal directed action. Semiotica, 71, 243–260. https://doi.org/10.1515/semi.1988.71.3-4.243.
Vanman, E. J. (2016). The role of empathy in intergroup relations. Current Opinion in Psychology, 11, 59–63. https://doi.org/10.1016/j.copsyc.2016.06.007.
Verbeek, P. (2008). Peace ethology. Behaviour, 145(11), 1497–1524.
de Waal, F. B. M. (1989). Peacemaking among primates. Harvard University Press.
de Waal, F. B. M. (2000). Primates—a natural heritage of conflict resolution. Science, 289(5479), 586–590.
de Waal, F. B. M. (2006). Primates and philosophers: how morality evolved. Princeton University Press.
de Waal, F. B. M. (2008). Putting the altruism back into altruism: The evolution of empathy. Annual Review of Psychology, 59, 279–300. https://doi.org/10.1146/annurev.psych.59.103006.093625.
de Waal, F. B. M., Aureli, F., & Russon, A. E. (1996). Consolation, reconciliation, and a possible cognitive difference between macaques and chimpanzees. In K. A. Bard, & S. T. Parker (Eds.), Reaching into thought. The minds of the great apes (pp. 80–110). Cambridge University Press.
de Waal, F. B. M., & Preston, S. D. (2017). Mammalian empathy: Behavioural manifestations and neural basis. Nature Reviews Neuroscience, 18(8), 498–509. https://doi.org/10.1038/nrn.2017.72.
de Waal, F. B. M., & van Roosmalen, A. (1979). Reconciliation and consolation among chimpanzees. Behavioral Ecology and Sociobiology, 5(1), 55–66.
Ward, J., & McMurray, R. (2015). The dark side of emotional labour. Routledge.
Wicherts, J. M., Veldkamp, C. L., Augusteijn, H. E., Bakker, M., Van Aert, R., & Van Assen, M. A. (2016). Degrees of freedom in planning, running, analyzing, and reporting psychological studies: A checklist to avoid p-hacking. Frontiers in Psychology, 7, 1832. https://doi.org/10.3389/fpsyg.2016.01832.
Young, C. (2018). Model uncertainty and the crisis in science. Socius, 4, 1–7. https://doi.org/10.1177/2378023117737206.
Note that the video dataset has been analyzed in a number of other bystander helping papers with other study objectives—i.e., the coordination between consolers (Bloch et al. 2018), and factors predicting intervention in mid-event conflicts (Liebst et al. 2019) and the associated victimization risk (Liebst et al. 2018).
An additional question to consider is whether the sex composition of those victimized was associated with the consolation outcome. In this analysis, we encountered a challenge: Out of the 49 contexts included, only three involved a female victim. This imbalance is known to diminish the statistical power of multilevel models (Olvera Astivia, Gadermann, & Guhn, 2019). Our analysis did not find an association between the sex composition of the victims and consolation, nor did it indicate that this variable moderated the effects of social affiliation or bystander sex (see online supplement for full output). However, these results should be interpreted with caution. Due to the low statistical power, it remains unclear whether the non-significant tests are due to an absence of true effects or insufficient power to detect any true effects.
