The Office of Population Research at Princeton University explores historic, present and future trends in population growth, decline and control, which in turn has consequences for network structure and interaction, economic viability, social mobility, governmental regulation and environmental capacity. One of the most famous experiments conducted in this field is the Princeton European Fertility Project, which “create[d] a quantitative record of the European fertility transition” and “determine[d] the social and economic circumstances that prevailed when the modern decline in fertility began in the hope of elucidating the causal mechanisms of the fertility transition.” This was conducted by collecting demographic data from 1,229 provinces all over Europe for the last two centuries and correlating socioeconomic outlooks of the time.

One of the most obvious reasons as to why population study is relevant to “Networks” is that each node generally depicts an individual within a larger context, which is the overall population. On the macro-level, the actual size of the network grows and declines based on the motives and decisions of that particular node at the micro-level (Schelling). This can be applied towards population in the question of whether or not to reproduce due to the cost-benefits outlays of rearing another child. Are there sufficient fruits for the labor involved? In fact, this has a direct game theory application in terms of choices and payoffs. For example, compare the costs of tuition at Cornell for parents if they rear another child versus splurging that money towards some R and R instead.

Or in the case of Princeton European Fertility Project’s focus on the 19th and 20th centuries’ population transition, how the payoffs for families to invest their eggs in half as many baskets became more advantageous. This period of population transition, when high birth and death rates moved towards low birth and death rates, with an underlying period of higher birth than death rates, resulted in large short-term population growth. The carrying capacity safety valve was released by migration to North America, opening up more “fixed” resources like land and offsetting otherwise finite constraints on the network.

More interestingly, however, is the implication of how birth rates ultimately caught up with death rates during population transitions. As shown in the second diagram below, there is generally a threshold after 10% of the population decreases their fertility rate which can be described as a ‘tipping point’ that catches on like wildfire to the rest of the population (Fahey, Gladwell). In line with Lesthaeghe and Wilson’s conclusions in 1968 to the Princeton European Fertility Project, Cornell Natural Resources Professor Tim Fahey attributes the cause of the ‘tipping point’ to a small component of secularized “free women” who broke traditional social norms and codes about fertility, creating a new smaller family size social convention that diffused rapidly to the rest of the population. Nevertheless, this has yet to be seen in places like sub-Saharan Africa, where the fertility rate remains consistently above 6.