Toward a Scientific History

Robert Aunger

Many scales: Many schools:

• Marxist• Structuralist• Deconstructionist • Anthropological • Psychological • Economic• Feminist

• Local• World/global• ‘Big’ history

No consensus?

History as ‘story-telling’

narrative interpretation of past events emphasizing –

• contingency

• human agency

• ‘big men’

(Etymology: Latin historia = “narrative, account, tale, story”)

No theory please!

“After a century of grand theory, from Marxism and Social Darwinism to structuralism and postmodernism, most

historians have abandoned the belief in general laws. We no longer search for grand designs and dialectics.

Instead, we concentrate on the particular and sometimes even the microscopic…not because we think we can see

the universe in a grain of sand but because we have developed an increased sensitivity to the complexities that differentiate one society or one subculture from

another.”

(Darnton 1999)

Historical regularities

(Turchin, 2005)

Historical progress

‘Arrow’ in history, resulting in increasing complexity over time

This progress attributed to –

• energy flows (LH Morgan, Leslie White, Chaisson)

• information accumulation (Lenski, Wright)

• dialectical mechanism (Hegel, Marx, Wallerstein)

(often related to technological advances)

Cycles in history

Recurrent patterns in the rising and falling sequence of some variable:

• civilizations/dynasties (Vico, Gibbon, Toynbee)

• population size/demographics (Turchin)

• economic waves (Kondratiev)

• spiritual development (Sarkar)

Leap theories

• Punctuated equilibrium (Eldredge & Gould)

• ‘Hopeful monster’ saltationism (Goldschmidt)

• Major transitions (Maynard Smith & Szathmáry)

Identification strategies1. Define periods of specific length beginning from

some arbitrary starting point

– e.g., BCE, the 60s

2. Pick events by particular characteristics

– e.g., the Middle Ages, the French Revolution

3. Begin with a theoretical criterion

– e.g., change in level of social organisation

‘Atoms’ of History

A science of history is possible if can identify class of objects analogous to the ‘natural kinds’ in other sciences (i.e., atoms, stars, genes, beliefs)

– periods?

Choices1. Use theoretical criterion as most likely to be scientific

2. Largest possible temporal scale to maximize chances of finding patterning in events – universal/cosmic

3. The only ‘currency’ applicable to cosmic/planetary/biological/cultural scale is energy; the common currency paying for all biological information or organisation in a self-organizing system is energy flow (Morowitz, 1979); transitions in rates of energy flow through thermodynamic systems are already established as the currency of ‘big’ history (Chaisson/Spiers)

4. Interested in explaining long-term increase in complexity, not medium-term cycles – so linear or leap theory

Maximum Entropy Production

(Paltridge, 1975; Attard, 2006; Niven, 2009)• A generalization of Boltzmann’s probability distribution to non-

equilibrium case• States that open thermodynamic systems with sufficient degrees of freedom (i.e., many elements) will converge to a

steady state at which the production of entropy is maximized given the constraints of the system

Systems far from equilibriumA wide variety of dynamical systems adjust to maximize

entropy production as a fundamental physical

necessity (Lineweaver, 2005)

Quantitative predictions

As an optimization solution, MEP ignores details of system dynamics, but nevertheless gives precise

predictions

E.g., MEP models of Earth’s climate include accurate predictions of –

• mean latitudinal air temperature

• fractional cloud cover

• meridional & vertical heat flux

• mean vertical air temperature profile

• historical latitudinal air temperature gradients

(Lorenz, 2004)

Darwinian Thermodynamics

(Ao 2005; Sella and Hirsch, 2005)

Applies Sewall Wright’s adaptive landscape idea to statistical

mechanics

Fitness or entropy is maximized, subject to constraints

Provides an intrinsically dynamic foundation for non-equilibrium thermodynamics,

which is currently limited by its foundation in equilibrium and steady-state descriptions (Ao,

2005)

MEP vs DT• Maximum Entropy Production Principle:

• a logical generalization of the second law of thermodynamics to non-equilibrium processes

• Empirically confirmed in studies of various systems of physical, chemical or biological origin

• Not contradicted by Prigorine’s minimum entropy production principle (which is a consequence of MEP in special circumstances)

• Appropriate when dynamics are difficult to observe(Martyushev and Seleznev, 2006)

• Darwinian Thermodynamic Theory:• the maximum entropy outcome is produced by the dynamics;

MEP doesn’t have a single outcome; instead the canonical (maximum) solution must be ‘chosen’ by convention

• not restricted to the linear near-equilibrium (Onsager) regime (Ao, 2005)

Steady-state response

Small flux perturbations cause control mechanisms to stabilize energy flow

rates, maintaining existing steady-state

(Kleidon, 2009)

Transitional response

If the boundary conditions shaping the optimum change, then a perturbation of the state can be amplified until the new

optimum is reached (i.e., positive feedback to the perturbation leads to a search for a new output level)

(Kleidon, 2009)

Dual responsesComplex thermodynamic systems are able

to –

• stabilize in the face of small fluctuations in energy flow (and so persist for some time)

• respond optimally to large fluctuations by finding a new steady state with higher (maximal) entropy production

The result historically should be a pattern of periodic jumps to new, higher levels of entropy production

Result

the fundamental unit of scientific ‘big’ history should be associated with a ‘leap’ in energy flow through a system far from

thermodynamic equilibrium

What are the internal mechanics of such leaps?

Control volume analysis

energy flows entropy

white elements = negative entropy

producers (i.e., perform useful

work)

black elements = positive entropy

producers (i.e. regions of high dissipation)

(Niven, 2009)

Flow-controlled system

Energy novelty

energy flows entropy

A random fluctuation in internal flux or external force will generally not lead to a sustained increase in entropy production

Energy novelty

entropy

A significant change in output is more likely to start with a new kind or level of energy flow in a system, due to a new way of extracting energy from the system’s surroundings. (Smil, 1994; Vermeij, 2004)

energy flow

energy flow

Structural adjustment

energy flow

entropy

Increased energy flow can cause new physical structures to form. Thermodynamic disequilibrium at point X induces a flow of energy toward an energy sink at point Y, producing a transient flow which increases disequilibrium at point Y. This new situation can cause a new or modified transport structure to form linking them (e.g., Belusov–Zhabotinsky reaction, self-organising nanostructures).

X Y

energy flow

Control

energy flow

entropy

• Control occurs in dynamical systems when a mechanism manipulates the inputs such that the stability of its output is increased. In particular, controls constrain the flow of energy through structures via feedback or interaction effects.

• Adjustments of control typically must follow the creation of new structures, eliminating some structures and modifying others to make them appropriate within the context of the system as a whole. (Freeman & Louçã, 2001; Turchin, 1977)

X Y

energy flow

A major energy novelty invokes several consequences, suggesting

that these groups of events are linked together and so should be

treated as inter-independent.

Such structured processes can be called ‘non-equilibrium steady-state

transitions’ (NESSTs).

NESSTs identify the time/place/mechanisms for the birth of new historical periods.

NESSTs

Scan the events covered by ‘big’ history (cosmological, geological, biological, cultural)

looking for this pattern:

Event associated with a sustained increase in energy flow (with entropy production) through a

system

followed ‘rapidly’ in the same area by an organisational event and a control event

which can be causally linked

Criteria for identifying historical ‘leap’

‘Energy flow density’:

the amount of free energy flowing through a gram of the relevant structure per second,

in ergs (Chaisson, 2001)

(NOTE: free energy [to do work] and entropy are linearly related in the Gibbs, Helmholtz and negative Massieu formulations, and so

good enough measure for general trends; e.g., S = (E-F)/T where ; S = entropy; E = internal energy; F = Helmholtz free energy; and T =

absolute temperature)

Entropy production measure

Cosmological transitions

NESSTENERGY

INNOVATION ORGANISATION CONTROLBEGINNIN

G DATEDURATION

(years)

ENERGY FLOW

DENSITY(ergs)

Atomic electron capture atomselectro-

magnetic forces

13.6997 BYA 1 x 10-11 0.005

Molecular charge exchange moleculesintra/inter-molecular

forces13.6996

BYA 1 x 10-5 .001

Stellar Proton-proton chain reaction

first generation stars

gravity vs gas pressure 13.5 BYA 100 2

Planetary Carbon/Oxygen/ Nitrogen cycle

solar systems with planets

gravity vs solar wind 13.3 BYA 100,000 20

Galaxy quasars/ black holes galaxies

gravity vs interstellar

wind13.0 BYA 100 M 50

Cosmological NESST

TRANSITION ASPECT NOVELTY FUNCTION DATE PLACE

Electron (Atomic)

Transitionenergy

electron capture by

nuclei

neutralize atomic charge, separate

matter and energy

13.6997 BYA

‘our’ universe

organisationatoms

(hydrogen, helium)

electrically neutral and hence

complex, stable matter

13.6997 BYA

‘our’ universe

controlelectro-

magnetic forces

nucleus/electron structural mediation

13.6997 BYA

‘our’ universe

Geological Transition

NESSTENERGY

INNOVATION ORGANISATION CONTROLBEGINNING

DATEDURATION

(years)

ENERGY FLOW

DENSITY(ergs)

Complex planet heat convection

layers of solid/liquid/ga

seous material

temperature/ pressure

differentials11.8 BYA 1 B 75

Population genetics = statistical mechanics

‘There is a close analogy between statistical thermodynamics and the evolution of allele frequencies under mutation, selection and random drift. This analogy brings together previous ideas in a general framework, and

justifies a maximum entropy approximation to the dynamics of quantitative traits.’

• Wright's formula for the stationary distribution of allele frequencies is analogous to the Boltzmann distribution in statistical physics.

• Population size plays the role of the inverse temperature and determines the magnitude of random fluctuations.

• Log mean fitness tends to increase under selection, and is analogous to (negative) energy.

• An entropy can be defined which measures the deviation from the distribution of allele frequencies expected under random drift alone.

• The sum gives a free fitness that increases as the population evolves towards its stationary distribution.

(Barton & Coe, 2009; building on Ao 2005, 2008)

Inevitable life

Self-organised systems produce more entropy, more quickly, than a disordered collection; thus MEP favours increasing

degrees of order

E.g., under the conditions of early Earth, life was the best way to release the build-up of geothermal energy. (Morowitz &

Smith, 2007)

Dissipative structures which produce high entropy – including living systems – can be viewed as highly probable

phenomena. (Dewar, 2005)

Biological Transitions

NESSTENERGY

INNOVATION ORGANISATION CONTROLBEGINNING

DATEDURATION

(years)

ENERGY FLOW

DENSITY(ergs)

Cell metabolism cell genetic code 3.5 BYA 500 M 1,000

Complex cell

mitochondria, chloroplasts,

lipidsEukaryote recombi-

nation/ sex 2 BYA 250 M 3,000

Multi-cellsecondary

aerobic reactions

multi-cellular organism

pattern codes;

neuronal nets

700 MYA 150 M 10,000

Biological NESST TRANSITION ASPECT NOVELTY FUNCTION DATE PLACE

Metabolic(Cell)

Transition

energy metabolism (e.g., photo-synthesis)

chemical reaction that produces

energy in a form harnessed by other

processes

3.75 BYA Planet Earth; deep sea vents?

organisation membrane protected micro-environment

3.6 BYA Planet Earth

control genetic code (e.g., RNA,

DNA)

self-catalyzing inter-generational

information storage system

3.25 BYA(?)

Planet Earth

‘metabolism first/compartment intermediate/replication last’ position

‘Culture evolves as the amount of energy harnessed per capita per year is increased,

or as the efficiency of the instrumental means of putting energy to work is

increased’

(Leslie White, 1949)

Cultural Transitions

NESSTENERGY

INNOVATION ORGANISATION CONTROLBEGINNING

DATEDURATION

(years)

ENERGY FLOW

DENSITY(ergs)

Tool(learned) tool

use and manufacture

parental unit cluster

tonally variant call system 25 MYA 10 M 20,000

Fire fire use bandnormative

social systems (culture)

2.5 MYA 1 M 40,000

Multi-tool tool kits tribe grammatical language 500,000 200,000 60,000

Complex tool

compound tools (e.g., bow-and-

arrow)

‘Big Man’ society

iconic representation

(cave art)50,000 20,000 70,000

Agriculturecultural

symbiosis (animal/plant

domestication)

chiefdom/ city-state

symbolic representation

(writing, mathematics)

10,000 5,000 85,000

Cultural NESST TRANSITION ASPECT NOVELTY FUNCTION DATE PLACEAgricultural (Chiefdom)Transition

energy animal domestication/

plant cultivation;metallurgy;

irrigation

increased regularity of dietary intake

(domesticated species); stronger tools; increased

ecological capacity

10,000 YBP

Middle East, Central

America, Asia

organisation chiefdom/ city-state

institutionalized leadership with power to

collect, store, and distribute surplus

resources

7,500 YBP

Middle East, Central

America, Asia

control symbolic representation

(cuneiform writing,

alphabet); legal system;

mathematics; money

sophisticated extra-somatic memory;

regulation of social relations on principles

other than kinship; system for managing technical

information; coordination of market exchange

5,000YBP

Middle East, Central

America, Asia

Technological Transitions

NESSTENERGY

INNOVATION ORGANISATION CONTROLBEGINNING

DATEDURATION

(years)GAP

(years)

ENERGY FLOW

DENSITY(ergs)

Machine

watermill/windmill; ‘Medieval agriculture

cycle’

autocratic (feudal) state

measuring instruments (e.g., clock)

1,000 500 3,000 100,000

Steam steam enginedemocratic

nation-state; corporation

canal, road and rail systems

250 50 250 500,000

Electric electricityinternational

cartels; industrial

research labs

telegraph/telephone;

railroad networks;

bureaucracy

150 30 50 1 M

Engineoil/internal combustion

engine

multinational agency/corporat

ion

mass media (radio, TV);

mass production

90 30 30 1.6 M

Nuclear nuclear reactors

global markets; World Wide

Webdigital media 40 25 20 3.2 M

Technological NESST TRANSITION ASPECT NOVELTY FUNCTION DATE PLACE

Machine (Second

Agricultural) Transition

energy watermill/ windmill; Medieval

“agriculture transition”

muscles largely replaced as energy

source; higher productivity levels

1,000 YBP

Europe, China

organisation autocratic (feudal) state

centrally directed super-institution

800 YBP

Europe, China

control “measuring instruments”

(mechanical clock, astrolabe);

printing press; science

“active” information processing by

artifacts; widespread

dissemination of information;

organized knowledge acquisition

500YBP

Europe, China

Hierarchy of timeEON ERA PERIODCosmological Physical Atomic

StellarPlanetaryGalaxy

Geological Complex planetaryAtmospheric

Terrestrial Biological CellComplex cellMulti-cell

Cultural ToolFireMulti-toolComplex toolAgriculture

Technological MachineSteamElectricEngineNuclear

Perasmology

‘Big’ history covers cosmological, planetary, biological and cultural history

– but as a single narrative (Christian, 2004)

Use of the NESST concept and non-equilibrium thermodynamics produces a

scientific ‘big’ history(Etymology: Perasma = Gk “transition or crossing”)

TechnologicalCulturalBiologicalPhysicalCosmological

0

1

2

3

4

5

6

7

8

9

10

024681012

Log Years Before Present

Lo

g Y

ears

/Erg

s

NESST Duration

NESST Gap

Energy Flow Density

Origin of life

-10

-8

-6

-4

-2

0

2

4

6

8

10

NESST Gap

NESST Duration

Energy Flow Density

10.14 10.13 10.12 10.11

Eras in PerasmologyGeo-

logical

Trend analysis

increasing complexity (more degrees of freedom)increasing hierarchyincreasing levels of energy disequilibrium

TIME

Terrestrial/OrganicNESSTs

accelerate

CosmologicalNESSTs

decelerate

Eras in Perasmology

ERA SOURCE OF POWER

INFORMATION INHERITANCE

SYSTEMSPhysical stellar fusion ––Geological convection ––Biological metabolism geneticCultural (wielded) tools + socialTechnological machines + artefactual

Major transitions in biology

Generalizing MTT

• NESST model extends ‘major transition theory’ (Maynard Smith and Szathmáry, 1995) into cosmological and geological time

• Turns MTT transitions into components of a larger explanatory framework (NESST)

• Shows how ‘egalitarian’ and ‘fraternal’ transitions (Queller, 1997) are related – as organisational and control elements of NESSTs, respectively

• e.g., multi-cellular organism is organisation in multi-cellular NESST; sexual reproduction is control element of complex cell NESST

Conclusions• The NESST concept and non-equilibrium

thermodynamics provide a framework – strongly grounded in physical and biological theory – which can be used to explain macro-historical trends since the origin of the universe

• This framework allows rigorous identification of historical ‘leaps’, which define periods beginning with a NESST

• ‘Big’ history becomes a scientific discipline: ‘Perasmology’

• Historical trends in energy, organisation and information are linked in a single framework, generalizing MTT

• NESSTs accelerate once information inheritance is invented

Acknowledgements

• Prof. Walter Alvarez, Earth and Planetary Sciences, University of California, Berkeley

• Prof. Ping Ao, Mechanical Engineering, University of Washington

• Prof. Eric Chaisson, Physics and Astronomy, Tufts University

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