Chapter 9 – Cooperation and Language Evolution

> Chapter 9 - Cooperation and Language Evolution


1. Introduction

In this article, we adopt the view that language evolved as a result of gradual evolutionary adaptation (Pinker, 2010). Firstly, higher social cooperation was developed as a reaction to the harshness of the natural environment. Then, language was developed as a reaction to the newly developed complex social environment.

Darwinism argues that natural selection is the process by which evolution occurs. Although popular culture has misconstrued it as a kind of race where might makes right, or a ‘survival of the fittest’, natural selection merely refers to the species adapting the best traits to survive in the local environment or against immediate circumstances (Gowlett, 2010). We are of the belief that cooperation helped our species to adapt and survive the harsh conditions of nature, thus forming the foundation for language as a later evolution in the human species.

Cooperation, defined as the willingness to share one’s mental state with another and to understand the mental states of others, seems to be the reason that language evolved. Egalitarianism became the dominant model for human society because the instinctual need to establish dominance has been channeled into more productive behaviour, making this system preferable for better childcare and survival. Intersubjectivity (the psychological relationship between people) in humans has been accentuated via natural selection, as living in large egalitarian groups has rewarded those who relate to others well (Knight & Power, 2012).

Due to the aforementioned conditions, humans can be said to have developed a practice of ‘cooperative mindreading’, as the mental states of others are inferred through indicators like eye gaze and facial expression. This has evolved into a quintessential part of human behaviour, and the communicative needs of humans become more complex. Therefore, language has evolved alongside these cooperative behaviours. The following paragraphs will then illustrate the factors of cooperation that have facilitated language evolution: reciprocity and altruism; joint attention; and social intelligence.

2. Relevance to Language Evolution

Cooperation evolved alongside language as a result of egalitarianism, but how did egalitarianism lead to the conditions for the emergence of language? When humans began living in larger groups, there was selection pressure for cooperative behaviour, and therefore social intelligence. Their offspring became more complex as a result of these pressures, and thus took longer to mature (Dunbar, 1996).

This increase in the burden of childcare led to those responsibilities being shared amongst the females (O’Connell, Hawkes, & Jones, 1999). However, childcare still took up enough energy such that the females were incentivised to include as many males as possible in their community to provide them with food. The increase in males would have increased sexual competition, implying a corresponding increase in inter-male violence.

In primate societies, sexual signals such as ovulation trigger inter-male violence (Goodall, 1986). In human societies, menstruation is that equivalent sexual signal, as it indicates which females are more immediately fertile. Males are then inclined to leave their partners to compete for these fertile females, then doing the same to her once other females signal their fertility.

However, egalitarian communities utilised strategies to circumvent that indication, thus dissuading violence as a means of sexual competition (Knight & Power, 2012). As such practice would be against the females’ interests, they isolate menstruating females from the males, preventing them from competing for the menstruating females. This display of physical solidarity sends a message to the males, ie. a law against taking menstruation as a trigger for sexual competition. This regulation of behaviour via cultural practice resulted in selection pressures for language as a method of enforcing these egalitarian laws, thus establishing the conditions necessary for language to evolve alongside cooperative behaviour.

3 Social Cooperation prior to Egalitarianism

For humans and animals in general, cooperation allows the species to tap into the different niche skills of individuals (Boyd & Richerson, 2009). In the past, it helped us to complete activities better with greater efficacy, until a conscious mind developed, which allowed for self-reflection (Torey, 2014). Language developed as a result of evolutionary pressure demanding a more sophisticated mechanism (Morgan, 2015). Cooperation is also observed in animals, but they did not develop cooperative mechanisms to the same extent that humans did; no social animal species has been observed to express the same diversity and depth of communication that is contained in human language (Fitch, 2011).

3.1 The Complex Social Environment of Fission-Fusion Societies

Before we get into the creation of language, we must first examine how sociality and social cooperation manifest among animal species in the first place. A primary aspect of social cooperation in humans is their ability to “dynamically switch among kinds of relationships according to their history, kinship, social support, the resource at stake, and the context” (Pinker, 2010). This form of complex social system, which allows for the constant merging and dissolving of relationships within a larger group, can be defined as a Fission-Fusion Society.

Fission is the process by which groups split apart, while Fusion is the process of individuals coming together. A Fission-Fusion Society is a group that “changes the size of their groups by means of fission and fusion of subunits” (Aureli et al., 2008). This form of social structure is not unique among humans as there are other species of social animals that merge together in large groups and reorient their relationships in smaller subunits. Usually, there are different tiers of subunits present in the species. For example, the social dolphins of Shark Bay have, as their smallest units, two or three males attached to a single female, and these groups will merge together into an even larger 2nd level alliance, which will merge into a third level alliance at the highest level (Connor, 2007).

Why this form of Fission-Fusion society arose in the first place is in reaction to the initial plethora of problems that social cooperation, and cooperating as a group, brought- namely “increased competition for all resources, including mates, and increased likelihood of disease and parasite transmission” (Alexander, 1989). Having the flexibility to split-into and reorient the whole group through shifting sub-units helps individuals cope with both the external environment situation (predators) and the social situation (competitors). Highly social species such as the previously mentioned Shark Bay dolphins, and the Hamadryas Baboon (Couzin & Laidre, 2009), will gather into sub-units and merge them into larger alliances in order to defend against predators and other alliances trying to steal their mates.

Yet, human beings display a form of social flexibility far outstripping that of any other animals, including social animal species such as chimpanzees. We have developed cooperation to the point of having a ”large size in combination with extensive cooperative behavior between unrelated individuals” (Melis & Semmann, 2010). We can interact socially with other humans whom we have never met before in our life, facilitating this interaction through language. R.D. Alexander (1989) hypothesizes that humans developed their sociality to such an extreme extent due to a mixture of runaway social competition and the ecological dominance of humans. Over time, as humans became the dominant species in their environment and external predatory threats decreased, the main problem individuals had to deal with was social competition within the species itself. Intensified social competition from competing sub-units became the new environment that humans had to adapt to, and as they developed better cognitive and cooperative capabilities, this created a feedback loop affecting the social environment as a whole. Pinker (2010) describes this process as filling a ‘cognitive niche’, where “initial increments in cooperation, communication, or know-how altered the social environment, and hence the selection pressures, for ancestral hominids”. Eventually, language was created to aid with sociality.

3.2 Brain size and Cooperation

In the previous section, we explored the possible evolutionary pressures leading up to the development of social cooperation, as well as the new social environment humans may have found themselves that they had to react to. But what primary change did they undergo on a biological level, and what measures might they have utilized in order to deal with the difficulties of such a change? This is what this section will explore.

In order for an animal to develop the cognitive capabilities necessary to facilitate higher levels of social intelligence (a factor for cooperation which will be elaborated later) they have to have a larger brain. Brain sizes are often used as an indicator of the animal’s cognitivity. This cognitivity can be calculated with the Encephalization Quotient (EQ), which is the ratio of the actual brain size of the animal being measured to the ‘expected’ size of the brain a similar-sized mammal would have. The larger the brain is, the more cognitive ability the animal is expected to have (Nave, Jung, Linnér, Kable, Koellinger, 2018). This is also correlated to social intelligence as mammals with higher social intelligence would require a higher cognitivity. For instance, humans have the highest EQ at 7.4-7.8 (Tang, 2008), while another social mammal, the Pacific White-sided Dolphin, has an EQ of 4.55. However, having large brains for higher intelligence does not come without its costs: the development of neural tissue is metabolically expensive, the anatomy of the female pelvis must be changed to account for the offspring’s larger head, and there are increased risks to both the mother and the child, such as painful births and risk of falling (Pinker, 2010). As a result of these costs, the process of childbirth becomes even more difficult, and cooperative breeding may be required to help offset the difficulties.

Cooperative breeding (as mentioned earlier) means that breeders who are the birth parents, are aided by helpers who were not directly involved in the breeding process but, nevertheless, aid with breeding. Humans are cooperative breeders, and they breed cooperatively to a far greater extent than any other animal in the animal kingdom (Zuberbühler, 2012). While there is currently no conclusive evidence that larger sizes in brains would lead to greater cooperative breeding, the species with larger EQ are found in highly cooperative fission-fusion societies (Lehmann, Korstjens, & Dunbar, 2006). This may thus correlate to this high level of cooperative breeding in humans, who have the highest EQ.

The degree and type of cooperative breeding varies amongst other animal species. In some species, infidelity may occur, and female breeders may be threatened by helpers who are trying to become breeders themselves  (Fan, Da, Luo, Xian, Chen & Du, 2017). Due to competition between females in the group, there may be an additional need for breeders to maintain their breeding status by suppressing other helpers and preventing them from becoming breeders, while providing prenatal and postnatal care for their offspring. This might spur on more social competition, which, in turn, reinforces the need for greater cognition to deal with such competition.

The heavy role and the needs of breeders may also pave their way for responsibilities to be shared amongst helpers. For example, while meerkat breeders take care of intimate needs in order to maintain their status, helpers will aid with provision of food, milk, prenatal care, and guarding the offspring (Sharp, English & Clutton-Brock, 2012). Another example is marmosets, who are some of the most cooperative breeders amongst primates as seen in how the father also helps out in breeding. Fathers in the animal kingdom do not usually aid in childbirth, but marmoset fathers “share the care responsibility and energetic load” (Ziegler, Sosa, & Colman, 2017). They may help out in the act of childbirth itself and cleaning up after the birth (e.g. biting off the umbilical cords) (Konner, 2016).

Through this cooperative web of breeders and helpers, a species was able to offset the high cost of an increased brain size, thus helping pave the way for greater cognitivity and social intelligence.

4    The Mechanisms of Language Evolution

So far, this article has discussed how cooperation and sociality are reflected in animal and human behaviour, based on the assumption that such behaviour is conditional for language to emerge. This section discusses how else that assumption may be proven, or better supported. Language did not emerge in its present form; the complexity of our current language systems had to be evolved.

Based on agent-driven models of language evolution (using language games), there are insights to be gained regarding the mechanisms through which language-like communication systems emerge, as well as the requirements for such mechanisms to be used successfully.

These mechanisms emerged in models that assume that these individuals are motivated to communicate with each other as successfully as possible using as little effort as possible. In essence, they wish to solve the problem of communicating as efficiently as they can through cooperative behaviour (albeit in self-interest), leading to the use of repair strategies and selectionism.

4.1    Repair Strategies

The results of those models suggest that the best way for individual hearers and speakers to collectively solve this problem is by use of repair strategies, which is a fundamental mechanism through which language may have emerged.

Within a community there exists a pool of solutions that can be used to fulfil a type of communicative task. Speakers draw from this pool so long as the task does not fall outside the capacity of any of these solutions. Should they encounter a task that does require more than what can be communicated with the known strategies available, they invent new solutions by means of repair strategies.

For example, if a speaker wishes to express a new concept, such as colour, they will either use a new word to describe it or take an old word and expand the number of possible meanings that word can represent to include that new concept. In this same example, when a hearer encounters this new word, or the old word used to describe this new concept, the hearer may, through context or feedback from the speaker, reconstruct what they believe to be the meaning of the new word, or similarly expand their definition of the old word. This mechanism is how new linguistic material may arrive in an individual’s inventory of solutions (Steels, 2009).

These solutions then can transmitted through a community through usage on an individual basis, until it has entered enough individual inventories to be considered part of the communal pool.

Note that repair strategies can also apply to grammaticalisation (Traugott & Heine, 1991) – when words are used in new ways rather than new meanings, e.g. verbs becoming nouns, nouns becoming verbs, grammaticalisation of these non-standard uses occurs when these types of usage become accepted convention due to selectionism.

4.2    Selectionism

Individual speakers encountering the same new concept may utilise the same approach (repair strategies), but arrive at different solutions. For example, they may end up with different words competing for the same meaning (synonymy), or having one word having their potential definitions expanded to mean a variety of meanings (polysemy). Selectionism explains how multiple solutions compete to enter the communal pool of solutions.

When there are multiple solutions competing for common use, individuals tend to prefer the most popular solution as it is the most likely to be understood and, thus, will have the highest chance of success (Steels, 2009). This leads to a snowball effect, in which words or grammaticalisations that are already popular will become even more so, resulting in the dominant solution entering into the communal pool of solutions. Note that this communal selection process is a side effect of individuals acting in self-interest, and not a conscious act of systemic change.

Selectionism also explains competition within repair strategies. When a combination of meanings needs to be expressed and one of the meanings has no word/sign attached to it, an individual may use either of two strategies to approach this communicative task – holistic coding or compositional coding (Steels, 2009). Either approach may invent a new word or expand the definition of an existing word to solve this task, but the target of the repair strategy differs.

Holistic coding applies repair strategies for that specific combination of meanings, while compositional coding applies them to the new meaning that has no existing word attached to it. The approach chosen depends on the circumstances in which the new meaning most frequently appears. Holistic coding will be applied if that specific combination of meanings occurs more frequently than the individual meaning, whereas compositional coding will be applied if the individual meaning occurs more frequently than that combination of meanings .

4.3    Emergence of Language Complexity

Complex language is an emergent outcome of repair strategies (which complexify the building blocks to form new strategies) being coupled with selectionism (which results in the consolidation of repair strategies).

As solutions become more complex, language too becomes more complex; holistic coding complexifies language at the level of the word, which allows multi-word utterances to form via holistic coding, and so on until grammaticalisation occurs (Steels, 2009). This progression occurred not only in the agent-based models, but also in the modern day when a community is lacking an effective communication system, such as in creole formation (Mufwene, 2001), or the case of Nicaraguan Sign Language.

4.4    Cooperation and the Mechanisms of Language Evolution

In these models, factors of cooperation (joint attention, theory of mind, and the ability to punish freeloaders) were found to be necessary in utilising these mechanisms (Wellens, Loetzsch, & Steels, 2008; Kaplan & Steels, 2001; Steels & Wang, 2008), and the models that lacked those cooperative factors were unable to achieve communicative success. Thus, the results of these models suggest that the mechanisms for language emergence are dependent on cooperative behaviour.

5    Factors of Cooperation

Social Cooperation is a complex process built out of many different traits and components. Some of these traits, or factors, have helped to facilitate the evolution of language. Below, we will focus on three factors that we believe to have played a part in language evolution: Reciprocal Altruism, Joint Attention, and Social Intelligence.

5.1    Reciprocal Altruism

5.1.1    Reciprocal Altruism in humans

‘Reciprocal Altruism’ refers to a process whereby costly cooperation among reciprocating partners is favored (Trivers, 1971). These include goods (sharing), services (helping) and information (informing) (Tomasello, 2008).

Altruism refers to actions that benefit others at the expense of oneself (Silk, 2013). It consists of helping, sharing and informing. Humans and animals both engage in helping, however sharing and informing are more common actions amongst humans. Although altruism displayed by animals conceals motives of self-interest, for humans it functions to strengthen social bonds. Actions such as helping in times of danger, sharing food, helping the sick, wounded, young and old, and sharing knowledge are norms displayed and observed in the daily lives of humans. These behaviours hold a greater meaning or purpose beyond the mere trading of functional items, expressing a desire to share, communicate and build relationships with one another (Logan, 2006). Human children, unlike apes, are able to engage in joint actions to achieve a collective goal. Children also point and show things to their parents or caregivers just for the contentment of doing so and because they want to share their interest with others (Tomasello & Carpenter, 2007). Children who commit such actions exhibit a deliberately cooperative or inherently altruistic attitude.

Furthermore, the inherent desire to share interest and to cooperate is conditional for language because this motivation forms the basis for intricate communication in humans (Logan, 2006). The nature of behaving cooperatively with one another renders language and complex communication possible among humans. Sharing and communicating can therefore possibly be auto-catalytic, where they cause each other to happen as a succession, resulting in the emergence of altruism and language.

5.1.2    Reciprocal altruism in animals

Animals, like humans, are able to recognise other individuals whom they have interacted with in the past, and some are even capable of doing a mental score-keeping (Cheney, 2011). This includes remembering past events that happened between them, regardless if these events were positive or negative; examples include any favours received or conflicts started between them. While it is common for humans to behave altruistically, the same behaviour is performed by animals mostly because any loss incurred to them is perceived as being counterbalanced by a potential return benefit in the future (König, 2005). This means that these altruistic actions are carried out mainly due to self-interest.

There are two types of reciprocity, namely, high-cost and low-cost reciprocity. Animals, like humans, are prone to committing acts of low-cost reciprocity (providing services that incur a lower opportunity cost on themselves) rather than carrying out high-cost ones (Brosnan & Waal, 2002). Instances of low-cost reciprocity include grooming, while those of high-cost reciprocity includes sharing food even when one’s own where survival is at stake. This can be seen in blood sharing activities performed by vampire bats, where they regurgitate blood to aid another hungry bat at the expense of starving themselves. This willingness to share blood is dependent on whether the bat they plan to aid has ever reciprocated any favors before.

Our view, though, is that ‘true’ altruism is seen in humans rather than animals because altruism’s function amongst humans lies in the strengthening social bonds. Helping others comes naturally to human children from an early age; this is seen from children offering help to those in need or initiating to share food with others without external stimulation, incentives, or promises of favors being reciprocated later. Such behaviour is then further reinforced by cultural and societal norms as they grow up (Tomasello, 2008).

The video below demonstrates the altruistic nature of human children. In this video, they are engaged in helping and enjoy doing so, especially when they see someone in need. On the other hand, if animals such as chimpanzees are under the same situation, they are less inclined to offer assistance.

The evolution of human language can therefore be seen as a result of social motivations stemming, not just from mere reciprocal altruism, but the desire to share and cooperate with one another. This is something not observed in other primates.

5.2    Joint Attention

5.2.1    Joint attention in humans

Joint attention occurs when two parties have a mutual interest in one another and a willingness to engage with each other (Carpenter & Liebal, 2011). This is a type of cooperative action (Carpenter & Call, 2013) that is important for proper conversation between two individuals to occur (Kwisthout, Vogt, & Dijkstra, 2008). Human infants first develop joint attention before they are 9 months old (Stahl and Striano, 2005), after which, their skills continue to develop eventually allowing them to become effective communicators when they grow up.

Joint attention can be observed through the action of sharing looks and gazes. These actions show a form of mutual acknowledgement and understanding of a particular shared object. Our view, for the purpose of this section, is that joint attention only truly occurs when individuals engaging in joint behaviour are doing so with social intent, for the sake of communication with one another. Therefore, there must be some form of engagement with the other party, a purposeful interaction, and a demand for their attention, so that communication can take place.

There are three components of joint attention; they are: checking attention, following attention, directing attention (Carpenter, Nagell, & Tomasello, 1998). Checking attention occurs when a person in a conversation looks to the other person to confirm his or her awareness and engagement with a single shared stimuli (Kwisthout et al., 2008). It is used to search for discrepancies between the attention of both parties, and to figure out possible actions to undertake (Kwisthout et al., 2008). It is said to occur prior to verbalisation and it affects both persons interpretation of what content they will communicate to one another (Carpenter et al., 1998). Following attention, on the other hand, allows people to share a frame of reference – referring to the spatial orientation of an object when locating an object. Finally, with directing attention, the listener decides on his own meaning after interpreting the content of the conversation. He will then communicate about the particular shared stimuli to the speaker. The picture below illustrates the phenomenon of joint attention through the sharing of looks and gazes.


Thus, joint attention allows coherent conversation because the parties involved in the conversation are able to focus on topics of the conversation (Kwisthout et al., 2008).

5.2.2    Joint attention in animals

For the case of animals, we take the stand that while animals possess joint attention, their version of it is limited. This limited ability for joint attention can be seen in experiments involving chimps and bonobos. These animals are seen to engage in typical joint attention behaviour such as gaze following. Furthermore, it is suggested that because they have ability for joint attention, they are able to engage in the social activity of playing (Wong & Kasari, 2012). In play, animals, as well as children, have to use specific behaviours to communicate their intentions. These actions require joint attention as the other party has to be engaged with the same stimuli to understand their actions and behaviour for meaningful communication.

The video below shows an instance of joint attention between 2 gorillas at play.


From the video, we see that joint attention allows the two gorillas to be engaged in play with the external stimuli (the ball). Without some level of joint attention, the gorillas will not be able to interact.

However, it is likely that joint attention is limited for the primates as they do not exhibit what can be directly understood as joint attentional behaviour. Human infants exhibit shared attention with declarative gestures that demand for the attention of the other party, thus proving that there is a demand for engagement with the other party. For chimpanzees and primates, on the other hand, experiments requiring proper engagement with their trainers show that primates may follow and share the gaze of their trainers, but do not produce declarative gestures. Therefore, in this video, it is possible that the gorillas do not want to purposely engage with the each other to share interest, but are simply engaging in partial joint attention where their attention is shared but still remains individualistic (Carpenter & Call, 2013).

Thus we conclude that for cooperation to take place, a higher form of joint attentional behavior, like those existing in humans, must be present. This ability to focus on individual or group attention, with the purpose of communicating with one another, has allowed humans to be able to interact properly with one another to facilitate the flow of information and ideas.

5.3    Social Intelligence

5.3.1    Social intelligence in humans

Social intelligence (SI) is the ability to get along well with others, winning their cooperation in the process (Albrecht, 2005). SI was observed in the early humans who cooperated in areas such as tool-making and in settings like around the fireplace. It is primarily present in humans, and it is this aspect of cooperation that differentiates us the most from other animals. SI is present when we display a sensitivity to the needs and interests of others, in our acts of altruism, when we show consideration towards others, and when we interact with others regardless of situation or setting.

Theory of Mind (ToM), a component of SI, is the ability to understand and predict the behaviour of others by seeing things from their perspective and understanding their mentality (Devaine, Hollard, & Daunizeau, 2014). It is a crucial aspect of social intelligence and cooperation as it is what forms the basis of social interactions and it helps humans understand each other. People with poor communicative abilities such as those with autism spectrum disorders (Baron-Cohen, 2000), attention deficit hyperactivity disorder, and schizophrenia, have been found to have lower SI and they do not perform as well in ToM tasks. There is a possible correlation between ToM and language disorders. Milligan, Astington, & Dack, (2007) suggest that there is a strong correlation between ToM and language development.

In this video, Simons demonstrates a test for ToM and shows how children in kindergarten (2-5 years of age) are able to pass the test. These children can understand the perspective of others at such a tender age.


With regards to cooperation, especially in parent-child relationships, it is found that children with higher participation in family discussions tend to perform better in ToM tasks. In a study by Ruffman, Slade and Crowe (2002), it was shown that the correlation between the mother’s usage of mental state utterances is consistent with the child’s ToM understanding. With stronger ToM, these children have a better development of language and stronger communicative abilities. This hypothesis can also be seen in reversed studies where ‘feral children’ who were neglected for years, such as classic cases Genie and Victor of Aveyron, had low communicative skills and were ultimately only able to pick up basic social skills. These children had communication issues due to the lack of social interaction, and could not grow abilities related to SI such as ToM; thus their language development was affected. These examples show how social interaction and cooperation, especially in the form of parent-child relationship, is crucial in language evolution. It is this strong cooperative structure between parents and children present in the human species that ensures children develop a stronger ToM, which is important to language evolution.

Language is ever-changing and evolving. One of the newest language that has evolved, the Nicaraguan Sign Language (NSL), owes its origins to social cooperation and SI that is embodied in humans. The birth of this new language is attributed to SI and cooperation between deaf individuals in Nicaragua.

A brief recount of its history is important to understand how SI and cooperation contributed to language birth. 

  • 1940s: No schools for the deaf. No socialisation amongst deaf students.
  • 1977:   First school for the deaf formed.
    • Students begin to socialise
  • 1986:  Club for social interactions formed.
    • Signers developed common lexicon
  • 1990s: Deaf community was formed (Yong, 2010)

From the history of NSL, we see that the deaf community established it on their own as a result of SI. They were drawn to interact with one another despite having no common language. It was from there that a new language was created.

The example of NSL reveals that language evolved because of the interaction between one’s exposure to their environment as well as the human species’ innate ability to interact with one another (Senghas & Coppola, 2001). The aforementioned innate abilities are related to SI as they show that humans have adapted and evolved specialised social-cognitive skills in order to live and exchange knowledge in social settings.

5.3.2    Social intelligence in animals

Is a Theory of Mind present in animals? Since the beginning of ToM studies, researchers have labelled it as a feature unique to humans. They postulate that animals have a lesser ability in understanding the intentions or goals of others. However, in recent years, there are scientists who have countered this argument (Wood, Glynn, Phillips, & Hauser, 2007). In this section, though, we take the stand that animals lack a high enough level of SI to have ToM. An experiment by Costes-Thiré, et al., (2015) reveals that primates are unable to differentiate between actions that are accidental or intentional. This supports the argument that animals are unable to truly understand the goals or intentions of the experimenters. We then argue that the level of ToM they exhibit is not as profound as humans. These findings can explain the reason for language evolution occurring to humans and not animals, as animals seemingly do not exhibit ToM, or at least perform a lower degree of it.

In another study on animals and primates, it was found that human children who did not receive schooling or developed literacy skills but were able to walk and have basic speech abilities for one year performed approximately the same as chimpanzees and orangutans in physical cognition. However, despite not developing proper literacy skills, the children greatly outstripped the non-human subjects in social cognitive tasks. The result of this study argues that that humans have such abilities mainly because we have a species-specific set of social-cognitive skills that evolved to allow us to participate and exchange knowledge in cultural groups (Herrmann, Call, Hernàndez-Lloreda, Hare, & Tomasello, 2007). This is largely due to the fact that humans evolved and gained stronger SI that then gave birth to other abilities such as communication via languages, showcasing how important cooperation is to language evolution.

6     Communicative Systems of Humans and Non-Human Primates

Human language has evolved alongside cooperative behaviour and has conferred humans the ability to communicate with a species-specific set of social-cognitive skills. It is argued that our language challenges evolutionary theory due to prominent differences between our communication system and that of our closest animal relatives (Seyfarth & Cheney, 2014). What exactly is the point of departure between both communicative systems and what features of human cognition has allowed for that?

6.1     Differences between Human Language and Non-Human Primate Communication

Languages obtain communicative power from being discrete, combinatorial, rule-governed, and open-ended computational systems (Seyfarth & Cheney, 2014). They are discrete as they comprise a plethora of learned, modifiable sounds. They are combinatorial as sounds consist of phonemes, which can be combined into words and then into sentences. They are rule-governed, and these grammatical rules serve to allow the meaning of each word to take on both its inherent meaning and its functional role in a sentence. Finally, they are open-ended as these rules allow for an infinite number of meanings, more than just those of its constituent words.

These features of human language have shown to be of stark contrast to that of non-human primates’ communication. With a comparatively smaller repertoire of calls, their vocalizations modify slightly during development (Hammerschmidt & Fischer, 2008). Various call types are also seldom given in combinations and if they do take place, there is not much evidence to show that individual calls play functional roles as agents, actions or patients (Seyfarth & Cheney, 2014). Primate vocalizations seem to restrict the amount of information that can be conveyed and thus, differ in the features of being discrete, combinatorial, rule-governed and open-ended communicative systems. Then, the next question one might pose would perhaps be, are there any similarities between the communicative systems of humans and primates?

6.2     Similar Neural Mechanisms

The aforementioned differences become the most apparent in call production, but similarities become obvious when considering neurological mechanisms that govern call perception. The combination of vocalizations and social knowledge contribute in forming a discrete, combinatorial, rule-governed and open-ended communicative system (Seyfarth & Cheney, 2014). It is even proposed that long before language evolved, such a system, along with social cognition, was already in place.

Humans and non-human primates share many neural mechanisms and they include the recognition of faces (Kanwisher, McDermott, & Chun, 1997; Tsao, Freiwald, Tootell, & Livingstone, 2006; Freiwald, Tsao, & Livingston, 2009) and voices (Belin & Zatorre, 2003; Petkov, Kayser, Steudel, Augath, & Logothetis, 2008), and for the multisensory integration of bimodal stimuli, especially voices and concurrent facial expressions (Ghazanfar & Eliades, 2014). These mechanisms are not likely to occur by accident but rather, it is possible that our ancestors and primates faced similar communicative challenges, and have since evolved similar mechanisms to tackle them.

6.3     Similar Social Functions of Communication

The communicative systems of humans and non-human primates are superficially different, with inherent similarities due to similar social functions. These functions can be derived at by looking at the features of non-human primate communication, with reference to recent research on wild baboons in the savannah woodlands of Africa.

Vocalizations of wild baboons are unique (Owren, Seyfarth, & Cheney, 1997), and baboons can recognise the voices of others through call production (Cheney & Seyfarth, 2007). Field playback experiments, a method involving the playing back of recorded animal sounds to other animals to observe their responses (Gregory, 2005), illustrate the following properties of baboons’ communicative system (Seyfarth & Cheney, 2014):

  •  An individual assesses the caller’s intention to communicate to her with the latter’s vocalization.
  • Calls help to facilitate social interactions.
  • Listeners are able to understand the meaning of a call by combining information from various sources: the call type, caller’s identity, previous events, and the caller’s and listener’s relationships with others.
  • Communication reveals what individuals know of one another.

Therefore, these shared social functions serve as reasons for the homologous neural mechanisms between humans and non-human primates. Baboon communication is perhaps not as superficial, but rather, is characteristic of a complex system of social knowledge.

6.4     Non-human Primate Communication: Discrete, Combinatorial, Rule-governed and Open-ended

Research has shown that baboons are capable of forming mental representations of call meanings, using discrete pieces of information, namely, the type of call, the caller’s identity, recent events, and the caller’s rank and kinship affiliation (Seyfarth & Cheney, 2014). Such discrete elements are then constrained by “rules” of call delivery, where the meaning of a message goes beyond that of the sum of meanings of its constituent elements. The limited number of signals that baboons have can also give rise to an unlimited number of meanings. Baboons are also capable of recognizing the calls of foreign individuals and assign meaning to them depending on the individuals’ ranks and kinship affiliations. Thus, these features contribute in showing how non-human primate communication can become discrete, combinatorial, rule-governed and open-ended.

The above evidence does not purport that the communicative system of baboons forms a language, or closely resemble that of human languages’ formal and structural properties. Instead, it suggests that humans and non-human primates share cognitive mechanisms and this is revealed through both communication systems.

Evidence has shown that a baboon’s reproductive success lies in its ability to form close, long-term bonds, and to recognize relations between others (Silk, et al., 2009). Therefore, natural selection favours those who are skilled in these respects, favouring discrete, combinatorial communication and social cognition.

Non-human primates exist in sophisticated social groups, where one’s reproductive success is dependent on its skills in establishing relationships. Animals are capable of having such complex communicative systems that are discrete, combinatorial, rule-governed and open-ended. It then seems compelling that when human language evolved from the communicative system of non-human primates, many of its prominent features were already in place.

7    Benefits of Language in Effective Cooperation

7.1    Collective Action Problems

Collective action refers to any situation where multiple individuals need to cooperate in order to achieve a greater good (Smith, 2010). An example of such collective goods are public goods or common-pool resources that are non-rival and non-excludable (Samuelson, 1954).

A Collective Action Problem (CAP) refers to the problems related to selfishness and lack of cooperation that ultimately hinders a group of people from achieving the best collective outcome (Smith, 2010). For example, the Prisoner’s Dilemma is a classic CAP. The scenario is quoted below (Milnovsky, 2014):

    Two members of a criminal gang are in solitary confinement. The prosecutors lack sufficient evidence to convict the pair on the principal charge, but they have enough to convict both on a lesser charge. Simultaneously, the prosecutors offer each prisoner a bargain. Each prisoner is given the opportunity either to betray the other by testifying that the other committed the crime, or to cooperate with the other by remaining silent. The offer is:


  • If A and B each betray the other, each of them serves two years in prison.
  • If A betrays B but B remains silent, A will be set free and B will serve three years in prison (and vice versa).
  • If A and B both remain silent, both of them will only serve one year in prison (on the lesser charge).

    It is implied that the prisoners will have no opportunity to reward or punish their partner other than the prison sentences they get and that their decision will not affect their reputation in the future. Because betraying a partner offers a greater reward than cooperating with them, all purely rational self-interested prisoners will betray the other, meaning the only possible outcome for two purely rational prisoners is for them to betray each other.

Aside from selfishness, there are limitations in logistics and information resources available for getting the best combination of individuals to work together (Smith, 2010). There also exists individuals who are considered ‘free-riders’, as they benefit from the collective good without contributing to the cost of providing it. This is a strong disincentive for other members of the community, discouraging from wanting more collective actions in the future (Smith, 2010).

Because free-riding and other selfish behaviour is difficult to manage in large groups, CAPs are supposed to be exceptionally difficult to solve in big communities. Yet, humans have been exceptional at resolving CAPs, by using communication to help suppress their own desire for individual gain. (Smith, 2010) It is also important to note that kinship had almost no influence on the result of a collective action.

It can then be said that humans have evolved at some point in time to approach CAPs differently from other animals. Theories surrounding this conclusion include the idea that collective action requires a great amount of facilitation via the use of symbols in the way we communicate (Smith, 2010).

This paper in particular (Smith, 2010) proposes that this ability in humans changes the cost-benefit ratios of achieving collective action, making it more favourable for humans to act together. Therefore, language, after evolution, has had a dramatic effect on collective action in humans.

7.2    Solutions to Collective Action Problems

7.2.1    Mutualism

Mutualism refers to individuals believing that their active cooperation will reap more personal benefits than free-riding (Smith, 2010). In this environment, ‘suckers’ (people who continue to actively invest their resources into collection) view free-riding as merely reaping any positive externalities and are not discouraged from contributing more (Smith, 2010).

In this scenario, it is rationally better to stop cooperating when too many people defect and become free-riders (Smith, 2010). Persuasive methods in such cases are also only effective when the rewards are clearly observable, so the best outcome available is difficult to achieve is larger group sizes (Smith, 2010). Additionally, this method requires strongly enforced norms about how the acquired benefits from a collective action will be equitably distributed (Smith, 2010). Therefore, there is a need for a ‘second-order’ CAP to establish such rules (Smith, 2010). Language helps to organise this solution, but may not necessarily resolve it.

7.2.2     Conditional Reciprocity

Conditional reciprocity is a solution where active participants only contribute to a collective action when there are no free riders (Smith, 2010). This ensures that only active contributors will enjoy the benefits of collective action, but it is difficult to confirm the lack of free riders in large groups (Smith, 2010). Language then becomes crucial to making this solution viable.

7.2.3    Indirect Reciprocity

Indirect reciprocity refers to partners in a community performing a collective action while other members determine whether they will be potential free-riders in the future (Smith, 2010). That show of collaboration between partners involves the use of reputation to facilitate trust, so this solution is considered more advanced than others.

This solution is excellent for quickly label many individuals according to their likeliness to reciprocate in the future. Yet, size is still a problem, as it is not realistic to gain a good estimate of all the members in a large community just by observing their interaction with others (Smith, 2010). Language is useful in this case by allowing observers to share their insights about different members in that community.

Potential complications include whether to regard a partner who betrays a defector can maintain their ‘cooperative’ image. A balance must be struck between loyalty and norm-adherence in order to appear trustworthy (Smith, 2010).

7.2.4    Signalling strategies

In this solution, individuals ‘show off’ qualities that make themselves good collaborators, such as a wealth of personal resources or a high level of productivity (Smith, 2010).
 It is prohibitively expensive for an individual to practice signalling towards a limited audience for extended periods of time. Language mitigates this by increasing the scale of outreach possible while reducing the amount of resources required (Smith, 2010).

7.3    Role of Language in Solving CAPs

7.3.1    Streamlining and Standardisation

Language helps in communicating about remote times and places, which increases the kinds of collective action that can be conducted successfully (Smith, 2010). Language also facilitates consensus and coordination in order to maintain adherence to norms. After that, language can help to define the agreed rules and accurately spread the knowledge of said norms (Smith, 2010). 
Furthermore, language helps to establish changes in norms when old norms reap lower collective benefits. It can persuasively explain the reasons behind new norms, which is necessary to overpower the current enforcement of old norms (Smith, 2010).

7.3.2    Enhances Rule Enforcement

Language makes enforcement of collectively beneficial norms more efficient: it makes identifying and punishing ‘free riders’ much easier, and verbal punishment requires fewer resources than physical punishment (Smith, 2010). It also assists in the categorisation of individuals according to their compliance with different sets of conventions, by creating and using various vocabulary.

7.3.3    Louder Broadcast

Recipients of an individual’s signalling strategy can use language to share knowledge about the signaller to others, making the signal more effective by attracting a larger audience without increasing the resources used (Smith, 2010).

7.3.4    Reputation Management

Language is useful in this case to communicate an individual’s history of cooperation in a detailed manner. It can help to explain reasons for past offences and show behavioural patterns (Smith, 2010). Language also adds another layer of assessment, as gossip can greatly reduce the amount of trust a community has in an individual.

8    Conclusion

In conclusion, language evolution is the result of humans having greater development of social skills as compared to animals, even our closest primate relatives and has likely been adapted based on our social motivations. It is likely that our social motivations, in form of the three factors mentioned above, allowed us to adapt and develop language. The features of the now-complex human language helps to resolve collective action problems. Humans can now police their societies more efficiently to prevent freeloading, and language seems to be the reason for the overwhelming success in solving collective action problems seen in human societies.

9. Bibliography

Albrecht, K. (2005). Social Intelligence: The New Science of Success. San Francisco: Hoboken : John Wiley & Sons, Inc., 2005.

Alexander, R. D. (1989). Evolution of the human psyche. The human revolution: Behavioural and biological perspectives on the origins of modern humans, 455-513.

Aureli, F., Schaffner, C., Boesch, C., Bearder, S., Call, J., Chapman, C., . . . Schaik, C. (2008). Fission‐Fusion Dynamics: New Research Frameworks. Current Anthropology, 49(4), 627-654. doi:10.1086/586708

Baron-Cohen, S. (2000). Theory of mind and autism: A review. International Review of Research in Mental Retardation. Vol. 23, 169-184. Retrieved from Autism Research Institute:

Belin, P., & Zatorre, R. J. (2003). Adaptation to speaker’s voice in right anterior temporal lobe. Neuroreport, 14(16), 2105–2109.

Boyd, R., & Richerson, P. J. (2009). Culture and the evolution of human cooperation. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1533), 3281-3288.

Brinck, I., & Liljenfors, R. (2012). The Developmental Origin of Metacognition. Infant and Child Development,22(1), 85-101.

Brosnan, S. F., & Waal, F. B. (2002). A proximate perspective on reciprocal altruism. Human Nature, 13(1), 129-152.

Camaioni, L., Perucchini, P., Bellagamba, F., & Colonnesi, C. (2004). The role of declarative pointing in developing a theory of mind. Infancy, 5, 291-308.

Carpenter, M., & Liebal, K. (2011). Joint attention, communication, and knowing together in infancy. Joint attention: New developments in psychology, philosophy of mind, and social neuroscience., 159-181.

Carpenter, M., Henning, A., Liszkowski, U., Striano, T., & Tomasello, M. (2004). Twelve-month-olds point to share attention and interest. Developmental Science, 7, 297-307.

Carpenter, M., Nagell, K., & Tomasello, M. (2013). How Joint Is the Joint Attention of Apes and Human Infants? Agency and Joint Attention, 49-61.

Cheney, D. L. (2011). Extent and limits of cooperation in animals. Proceedings of the National Academy of Sciences,108, 10902-10909.

Cheney, D., & Seyfarth, R. (2007). Baboon Metaphysics. University of Chicago Press.

Connor, R. C. (2007, 04). Dolphin social intelligence: Complex alliance relationships in bottlenose dolphins and a consideration of selective environments for extreme brain size evolution in mammals. Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1480), 587-602. doi:10.1098/rstb.2006.1997

Costes-Thiré, M., Levé, M., Uhlrich, P., Pasquaretta, C., De Marco, A., & Thierry, B. (2015). Evidence that monkeys (Macaca tonkeana and Sapajus apella) read moves, but no evidence that they read goals. Journal Of Comparative Psychology 2015 Aug; Vol. 129 (3), 304-310.

Couzin, I. D., & Laidre, M. E. (2009, 08). Fission–fusion populations. Current Biology, 19(15). doi:10.1016/j.cub.2009.05.034

Devaine, M., Hollard, G., & Daunizeau, J. (2014). Theory of Mind: Did Evolution Fool Us? PLoS ONE. Feb2014, Vol. 9 Issue 2, 1-12.

Dunbar, R. I. M. (1996). Grooming, gossip and the evolution of language. London: Faber and Faber/Cambridge MA: Harvard University Press.

Fan, L., Da, X., Luo, J., Xian, L., Chen, G., & Du, B. (2017). Helpers of the Giant Babax cheat for an immediate reward when they provision the brood. Journal of Ornithology, 159(1), 245-253. doi:10.1007/s10336-017-1496-x

Fitch, W. T. (2011). Unity and diversity in human language. Philosophical Transactions of the Royal Society B: Biological Sciences, 366(1563), 376-388. doi:10.1098/rstb.2010.0223

Freiwald, W. Y., Tsao, D. Y., & Livingston, M. S. (2009). A face feature space in the macaque temporal lobe. Nature Neuroscience, 12(9), 1187-1196.

Ghazanfar, A. A., & Eliades, S. J. (2014). The neurobiology of primate vocal communication. Current Opinion in Neurobiology, 28, 128–135.

Gowlett, J. (2010). Firing Up the Social Brain. Social Brain, Distributed Mind, 340-366.

Gregory, R. (2005). Primate Language and the Playback Experiment, in 1890 and 1980. Journal of the History of Biology, 38(3), 461-493.

Hammerschmidt, K., & Fischer, J. (2008). Constraints in primate vocal production. In G. U., & O. K., The Evolution of Communicative Creativity: From Fixed Signals to Contextual Flexibility (pp. 93-120). The MIT Press.

Herrmann, E., Call, J., Hernàndez-Lloreda, M. V., Hare, B., & Tomasello, M. (2007). Humans Have Evolved Specialized Skills of Social Cognition: The Cultural Intelligence Hypothesis. Science 07 Sep 2007: Vol. 317, Issue 5843, 1360-1366.

Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. The Journal Of Neuroscience: The Official Journal Of The Society For Neuroscience, 17(11), 4302–4311.

Kaplan, F., & Steels, L. (2001). AIBO’s first words. The social learning of language and meaning. Evolution of Communication, 4(1).

Konner, M. (2016). Women after all: Sex, evolution, and the end of male supremacy. New York: W.W. Norton & Company.

Knight, C. & Power, C. (2012) Social conditions for the evolutionary emergence of language. In Tallerman, M. & Gibson, K.R. (Eds.), The Oxford Handbook of Language Evolution. (346-59). New York: Oxford University Press.

König, E. (2005). Reciprocity in Language: Cultural Concepts and Patterns of Encoding. Uhlenbeck Lecture 23, 1-27.

Kwisthout, J., Vogt, P., Haselager, P., & Dijkstra, T. (2008). Joint attention and language evolution. Connection Science,20(2-3), 155-171.

Lehmann, J., Korstjens, A. H., & Dunbar, R. I. (2006). Fission–fusion social systems as a strategy for coping with ecological constraints: A primate case. Evolutionary Ecology, 21(5), 613-634. doi:10.1007/s10682-006-9141-9

Logan, R. K. (2006). The extended mind model of the origin of language and culture. Evolutionary Epistemology, Language and Culture, 149-167.

Marino, L. (2004). “Cetacean Brain Evolution: Multiplication Generates Complexity”. International Society for Comparative Psychology (17): 1–16.

Melis, A. P., & Semmann, D. (2010, 09). How is human cooperation different? Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1553), 2663-2674. doi:10.1098/rstb.2010.0157

Milligan, K., Astington, J. W., & Dack, L. A. (2007). Language and theory of mind: Meta-analysis of relationship between language ability and false belief understanding. Child Development. Vol. 78, Issue 2, 622-646.

Milovsky, Nicholas. “The Basics of Game Theory and Associated Games”. Retrieved 11 February 2014.

Morgan, T. J., Rendell, L. E., Chouinard-Thuly, L., Street, S. E., Lewis, H. M., & Laland, K. N. (2015). Experimental evidence for the co-evolution of hominin tool-making teaching and language. Nature Communications, 6, 6029, 8.

Mufwene, S. S. (2001) The Ecology of Language Evolution. Cambridge: Cambridge University Press.

Mundy, P., Block, J., Delgado, C., Pomares, Y., Vaughan Van Hecke, A., & Parlade, M. V. (2007). Individual Differences and the Development of Joint Attention in Infancy. Child Development, 78(3), 938-954.

Nave, G., Jung, W. H., Linnér, R. K., Kable, J. W., & Koellinger, P. D. (2018). Are Bigger Brains Smarter? Evidence From a Large-Scale Preregistered Study. Psychological Science, 30(1), 43-54. doi:10.1177/0956797618808470

O’Connell, J. F., Hawkes, K., and Blurton Jones, N. G. (1999). Grandmothering and the evolution of Homo erectus. Journal of Human Evolution, 36, 461–485.

Owren, M. J., Seyfarth, R. M., & Cheney, D. L. (1997). The acoustic features of vowel-like grunt calls in chacma baboons (Papio cyncephalus ursinus): implications for production processes and functions. The Journal Of The Acoustical Society Of America, 101, 2951–2963.

Petkov, C. I., Kayser, C., Steudel, T. W., Augath, M., & Logothetis, N. K. (2008). A voice region in the monkey brain. Nature Neuroscience, 11, 367-374.

Pinker, S. (2010). The cognitive niche: Coevolution of intelligence, sociality, and language. Proceedings of the National Academy of Sciences, 107(Supplement 2), 8993-8999.

Samuelson, P.A. (1954), ‘The Pure Theory of Public Expenditure,’ Review of Economics and Statistics, XXXVI, pp. 387-389.

Schartman, S. (2013). Discourse Communities and the Language of Pain. Department of Cognitive Linguistics, Case Western Reserve University, Cleveland, OH, 1-30.

Senghas, A., & Coppola, M. (2001). Children Creating Language: How Nicaraguan Sign Language Acquired a Spatial Grammar. Psychological Science, 7/1/2001, Vol. 12, Issue 4, 323-328.

Seyfarth, R. M. & Cheney, D. L. (2014). The evolution of language from social cognition. Current Opinion in Neurobiology, 25 (5-9).

Sharp, S. P., English, S., Clutton-Brock, T. H. (2012). “Maternal investment during pregnancy in wild meerkats”. Evolutionary Ecology. 27 (5): 1033–1044. doi:10.1007/s10682-012-9615-x

Silk, J. B. (2013). Reciprocal altruism. Current Biology, 23(18), 2.

Silk, J. B., Beehner, J. C., Bergman, T. J., Crockford, C., Engh, A. L., Moscovice, L. R., . . . Cheney, D. L. (2009). The Benefits of Social Capital: Close Social Bonds among Female Baboons Enhance Offspring Survival. Proceedings: Biological Sciences, 276(1670), 3014-3099.

Smith, E. A. (2010). Communication and collective action: language and the evolution of human cooperation. Evolution and Human Behavior, 31 (231–245).

Sodian, B., & Kristen-Antonow, S. (2015). Declarative joint attention as a foundation of theory of mind. Developmental Psychology, 51(9), 1190-1200.

Stahl, D., & Striano, T. (2015). Joint attention in the first year: The coordination of gaze and affect between 7 and 10 months of age. Proceedings of the Fifth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, 2.

Steels, L. (2009) Is sociality a crucial prerequisite for the emergence of language? In Botha, R. & Knight, C. (Eds.), The Prehistory of Language. (37-57). New York: Oxford University Press.

Steels, L., & Wang, E. (2008). Self-interested agents can bootstrap symbolic communication if they punish cheaters. In The Evolution Of Language (pp. 362-369).

Tang, B.L. (2006). Molecular genetic determinants of human brain size. Biochemical and biophysical research communications, 345 3, 911-6.

Tomasello, M. (2008). Origins of human communication. Cambridge, Mass: MIT Press.

Tomasello, M., & Carpenter, M. (2013). Shared intentionality. Developmental Science,10(1), 121-125.

Torey, Z. L. (2014). The conscious mind. Cambridge, Massachusetts: The MIT Press.

Traugott, E. C. & Heine, B. (1991). Approaches to Grammaticalization. Amsterdam: John Benjamins Publishing.

Trivers, R. L. (1971). The Evolution of Reciprocal Altruism. The Quarterly Review of Biology, 46(1), 35-57.

Tsao, D. Y., Freiwald, W. A., Tootell, R. B., & Livingstone, M. S. (2006). A cortical region consisting entirely of face-selective cells. Science, 311, 670-674.

Wellens, P., Loetzsch, M., & Steels, L. (2008). Flexible word meaning in embodied agents. Connection Science, 20(2 & 3):173-191.

Wong, C., & Kasari, C. (2012). Play and Joint Attention of Children with Autism in the Preschool Special Education Classroom. J Autism Dev Disord, 42(10), 2152-2161.

Wood, J. N., Glynn, D. D., Phillips, B. C., & Hauser, M. D. (2007). The perception of rational, goal-directed action in nonhuman primates. Science, 317, 1402-1405.

Yong, E. (2010). New Nicaraguan sign language shows how language affects thought. Retrieved from Discover:

Ziegler, T. E., Sosa, M. E., & Colman, R. J. (2017). Fathering style influences health outcome in common marmoset (Callithrix jacchus) offspring. Plos One, 12(9). doi:10.1371/journal.pone.0185695

Zuberbühler, K. (2012). Cooperative breeding and the evolution of vocal flexibility. In The Oxford handbook of language evolution.

Skip to toolbar