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it is no accident therefore that the physical and the social mirror each other,
Just as raising the temperature of a gas or liquid increases the rate in the number of collisions between molecules, so increasing the size of a city increases the rate and number of interactions between its citizens.
the proverbial image of a “melting pot,” originally applied to New York City, is an apt expression of this metaphor.
Although social and physical networks share common generic features such as being fractal-like, space filling, and having invariant terminal units, there are some essential differences. A major one that has huge consequences is the way in which the sizes and flows within the networks scale as one progresses down through their fractal-like hierarchies.18
The strengths of social interaction and the flows of information exchange are greatest between terminal units (that is, between individuals) and systematically decrease up the hierarchy of group structures
Sizes and flows systematically increase from terminal units (houses and buildings) up through the network, leading to sublinear scaling and economies of scale
a further consequence of this kind of network architecture is the systematic slowing down of the pace of life as the size of organisms increases.
Knowing the inverse linkage between these two different kinds of networks, it should come as no great surprise that precisely the opposite behavior arises in social networks. Rather than the pace of life systematically decreasing with size, the superlinear dynamics of social networks leads to a systematic increase in the pace of life:
This effective speeding up of time is an emergent phenomenon generated by the continuous positive feedback mechanisms inherent in social networks in which social interactions beget ever more interactions,
Everything nowadays is ultra, everything is being transcended continually in thought as well as in action.
Goethe railing about the increasing pace of life and its shallowing effect.
In 1930 the great economist John Maynard Keynes wrote: For the first time since his creation man will be faced with his real, his permanent problem—how to use his freedom from pressing economic cares, how to occupy the leisure, which science and compound interest will have won for him, to live wisely and agreeably and well.
Instead of giving us more time, “science and compound interest” driven by “technologists working for fifty hours a week” have, in fact, given us less time.
Rather than being bored to death, our actual challenge is to avoid anxiety attacks, psychotic breakdowns, heart attacks, and strokes resulting from being accelerated to death.
Zahavi discovered the surprising result that the total amount of time an average individual spends on travel each day is approximately the same regardless of the city size or the mode of transportation. Apparently, we tend to spend about an hour each day traveling, whoever and wherever we are.
the increase in transportation speed resulting from the marvelous innovations of the past couple of hundred years has not been used to reduce commuting time but instead has been used to increase commuting distances
even if an individual’s daily commute time is less than an hour, then he or she instinctively makes up for it by other activities such as a daily constitutional walk or jog.
Because walking speed is about 5 kilometers an hour, the typical extent of a “walking city” is about 5 kilometers across
“There are no city walls of large, ancient cities (up to 1800), be it Rome or Persepolis, which have a diameter greater than 5km or a 2.5km radius.
This surprising observation of the approximately one-hour invariant that communal human beings have spent traveling each day, whether they lived in ancient Rome, a medieval town, a Greek village, or twentieth-century New York, has become known as Marchetti’s constant
We are subliminally influenced by the presence of other individuals and infected by the increasing pace of life, unconsciously finding ourselves in a hurry to get to a store, the theater, or to meet a friend.
data confirm that walking speeds do indeed increase with city size following an approximate power law, though its exponent is somewhat less than the canonical 0.15, being closer to 0.10
An unexpected expression of this hidden dynamic is the recent introduction of fast lanes for walking in the British city of Liverpool.
Despite the obvious difficulties when it comes to social systems, social scientists have been very imaginative in devising analogous quantitative experiments to inspire and test hypotheses, and these have proven to give insight into social structure and dynamics.
social interactions do indeed underlie the universal scaling of urban characteristics.
the accelerating pace of life originates in the increasing connectivity and positive feedback enhancement in social networks as city size increases.
The size of an average individual’s modular cluster of acquaintances who interact with one another is an approximate invariant—it doesn’t change with city size.
So even in large cities we live in groups that are as tightly knit as those in small towns or villages.
There is, however, an important qualitative difference in the nature of these modular groups in villages relative to those in large cities.
in a city we are freer to choose our own “village” by taking advantage of the much greater opportunity and diversity afforded by a greater population and to seek out people whose interests, profession, ethnicity, sexual orientation, and so on are similar to our own.
the properties of cities emerge from social collisions and the chemistry of and between people.
the number of visitors should scale inversely as the square of both the distance traveled and the frequency of visitation.
if the distance traveled multiplied by the frequency of visits to any specific location is kept the same, then the number of people visiting also remains the same
In assessing the performance of a particular city, we therefore need to determine how well it performs relative to what it has accomplished just because of its population size.
Once a city has gained an advantage, or disadvantage, relative to its scaling expectation, this tends to be preserved over decades.
the total number of establishments in each city regardless of what business they conduct turns out to be linearly proportional to its population size. Double the size of a city and on average you’ll find twice as many businesses.
the total number of employees working in these establishments also scales approximately linearly with population size: on average, there are only about 8 employees for every establishment,
doubling the size of a city results in doubling the total number of establishments, but only a meager 5 percent increase in new kinds of businesses.
This is an important observation because it shows that increasing diversity is closely linked to increasing specialization, and this acts as a major driver of higher productivity following the 15 percent rule.
despite the unique admixture of business types for each individual city, the shape and form of their distribution is mathematically the same for all of them.
The universality is driven by the constraint that the sum total of all the different businesses in a city scales linearly with population size, regardless of the detailed composition of business types or of the city.
It goes under many different names including preferential attachment, cumulative advantage, the rich get richer, or the Yule-Simon process. It is based on a positive feedback mechanism in which new elements of the system (business types in this case) are added with a probability proportional to the abundances of how many are already there.
The general rule is that business types whose abundances scale superlinearly with population size systematically rise in their rankings, whereas those that scale sublinearly systematically decrease.
traditional sectors such as agriculture, mining, and utilities scale sublinearly; the theory predicts that the rankings and relative abundances of these industries decrease as cities get larger.
informational and service businesses such as professional, scientific, and technical services, and management of companies and enterprises, scale superlinearly and are consequently predicted to in...
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all socioeconomic contributions to social metabolism that underlie growth, including wealth creation and innovation, scale in approximately the same way following the classic superlinear power law with a common exponent of approximately 1.15.
the total social metabolic rate of a city must likewise scale superlinearly with an exponent of 1.15.
In contrast to the situation in biology, the supply of metabolic energy generated by cities as they grow increases faster than the needs and demands for its maintenance.
The bigger the city gets, the faster it grows—a classic signal of open-ended exponential growth.
sublinear scaling and economies of scale that dominate biology lead to stable bounded growth and the slowing down of the pace of life, whereas superlinear scaling and increasing returns to scale that dominate socioeconomic activity lead to unbounded growth and to an accelerating pace of life.
The mechanisms that have traditionally been suggested for understanding companies can be divided into three broad categories: transaction costs, organizational structure, and competition in the marketplace.
