Week 1: Economics and Science
Many connect problems of modern economics to science
o Within those who believe this – two opposed groups
First comprises those who think that the problems with the discipline
arise just because an economic science is infeasible
it’s the concern that to be scientific leads economists astray
Second group think that problems arise because economics has yet to
realize its full scientific potential
o Fundamentally both groups associate science with use of mathematical methods
o their contrasting expectations concerning the possibility
of an economic science primarily reflect different
expectations concerning the possibility of gaining
insight using mathematical models
o My contrary view (author’s) is that
o 1) the use of mathematics is irrelevant to the
question of whether a discipline qualifies as
science.
o 2) a science of economics is entirely feasible,
o 3) the current emphasis on formalism in modern
economics mostly obstructs the potential of
economics for realizing its potential as a
successful science
o Author sides with first group in being optimistic about possibilities of successful
economic science – but holding contrasting conception of science
o Author sides with second group in thinking that the emphasis on
formalism is unhelpful in modern economics
Casual versus predictionist accounts of science
o Read again
Week 2: Competing Conceptions of Science – Causalist v. Predictionist Account
Causalist view – able to render intelligible key elements of natural scientific practice
including the experiment and account for its significance
Whereas predictionist view is incapable of making sense of the experiment
We can only understand importance of the experiment and the associated aim of
generating a ‘closed system’ in certain of the natural sciences if we recognize world is
typically ‘open’ and ‘structured’
Causalist view – associated w/ recognition that world is structured – that world not only
made of events relationships and events b/w them but also constituted by underlying
causal mechanisms that have independent existence
, Causalist conception science + scientific explanation – centrally concerned w/
movement from surface phenomena to an understanding of causal mechanisms
underlying them and generative of them
o No one single approach – science is about understanding the causes of a
problem – requires different tools and approaches
o Ex. Causalist view – if you have a headache and it goes from an aspirin – figure
out why the aspirin makes you not have a headache – see the chemicals that fix
it
Closed system – one causal mechanism that is isolated – you can observe it without any
interference – to ensure closed system: intrinsically stable (acts in same way all the
time), need to be isolatable, things need to act in isolation
Open system – type of system that is like the
Predictionist view: big thing – emphasis on identification of event regularities – but none
in social realm – misrepresentation
o Predictionist view: argue that only w use of mathematical modeling we can claim
we are taking a scientific approach to reach social phenomena
Trying to identify event regularity and stable functions – predict future –
not helpful approach – provides event regularities
Mathematical modelling used because the math will provide only stable
functions
Predictionist view leads to insistent on mathematical modelling
Why the causal conception of science is more reasonable account of what goes on in
science that predictionist conception:
o Most obvious observation – outside astronomy most of the event regularities
regarded as of interest to natural science are restricted to conditions of well-
controlled experiment
o It’s more/less only in experimental contexts that the predictionist worldview
even appears to hold up – yet successful natural science – hardly restricted to
situations of experimental control
o Even the situation of well-controlled experiment – provides relative support to
Causalist rather than the predictionist account of science
Outside astronomy only time we can be sure of constant conjunctions occurring are in
our experiments:
o Shows us nature of experiment – ensures that irrelevant variables which could
influence outcome are absent
o It’s useful to design/conduct experiments b/c cause equals constant conjunction
only when other things are equal and in nature – other things are never equal –
the natural world is an open system and experiment establishes a closed system
Implications –
o A central aim of the experiment is to understand causal mechanisms not
simply identify event regularities
Real world just not just consist of what we experience or what happens –
it also included the mechanisms that make things happen
, o The importance of tendencies
Tendencies are potentialities which may be exercised or in play w/o being
straightforwardly realized or manifest in any particular outcome
Understanding of causal mechanisms allows us to manipulate/anyway
trigger those mechanisms outside the experiment – where event
regularities typically don’t hold
o Developing our understanding of the nature of science
An essential moment in natural science involves identifying/
understanding causes of phenomena of interest – the practice of
successful event prediction not an essential feature
An understanding of causal mechanisms (ex. Diseases) is what’s typically
required for helping us make world a better place – understanding the
working mechanisms that cause symptoms of illness allow us to intervene
and provide an antidote to the problem
o The Key move in scientific practice
Once Causalist view of science accepted – then it can be recognized that
the essential movement in science –
one whereby drawing on analogies /metaphor we shift from a
conception some phenomena of interest to conception some totally
different type of thing, mechanism structure/condition that is responsible
for given phenomena
It’s a movement paradigmatically from a surface phenomenon to some
deeper causal thing
o Explanatory power v. prediction
Explanatory rather than predictive power must become dominant
criterion of theory adequacy – while objective of assessing reality of the
posited mechanism has to be explicitly acknowledged
Stratification of Nature and Emergence
o If one key aspect to an adequate account of science involves recognising the
existence of real causal mechanisms existing beneath events
o another aspect involves recognising that the natural world is ordered in layers
o idea of layering or stratification of nature is linked to the theory of emergence –
one stratum is emergent from another when it is ontologically dependent on it
but not reducible to it
o emergent stratum has its own laws which cannot be deduced from those of the
stratum from which it is emergent
Change in Scientific Understanding + Change in Material being studied by science
o Further key element to an adequate account of science involves recognizing that
change is possible both at level of our understanding of nature of objects we
study and level of material we study
o No science remains static – scientific theories are continuously changing
o Important to recognize material scientists’ study also not static
Many connect problems of modern economics to science
o Within those who believe this – two opposed groups
First comprises those who think that the problems with the discipline
arise just because an economic science is infeasible
it’s the concern that to be scientific leads economists astray
Second group think that problems arise because economics has yet to
realize its full scientific potential
o Fundamentally both groups associate science with use of mathematical methods
o their contrasting expectations concerning the possibility
of an economic science primarily reflect different
expectations concerning the possibility of gaining
insight using mathematical models
o My contrary view (author’s) is that
o 1) the use of mathematics is irrelevant to the
question of whether a discipline qualifies as
science.
o 2) a science of economics is entirely feasible,
o 3) the current emphasis on formalism in modern
economics mostly obstructs the potential of
economics for realizing its potential as a
successful science
o Author sides with first group in being optimistic about possibilities of successful
economic science – but holding contrasting conception of science
o Author sides with second group in thinking that the emphasis on
formalism is unhelpful in modern economics
Casual versus predictionist accounts of science
o Read again
Week 2: Competing Conceptions of Science – Causalist v. Predictionist Account
Causalist view – able to render intelligible key elements of natural scientific practice
including the experiment and account for its significance
Whereas predictionist view is incapable of making sense of the experiment
We can only understand importance of the experiment and the associated aim of
generating a ‘closed system’ in certain of the natural sciences if we recognize world is
typically ‘open’ and ‘structured’
Causalist view – associated w/ recognition that world is structured – that world not only
made of events relationships and events b/w them but also constituted by underlying
causal mechanisms that have independent existence
, Causalist conception science + scientific explanation – centrally concerned w/
movement from surface phenomena to an understanding of causal mechanisms
underlying them and generative of them
o No one single approach – science is about understanding the causes of a
problem – requires different tools and approaches
o Ex. Causalist view – if you have a headache and it goes from an aspirin – figure
out why the aspirin makes you not have a headache – see the chemicals that fix
it
Closed system – one causal mechanism that is isolated – you can observe it without any
interference – to ensure closed system: intrinsically stable (acts in same way all the
time), need to be isolatable, things need to act in isolation
Open system – type of system that is like the
Predictionist view: big thing – emphasis on identification of event regularities – but none
in social realm – misrepresentation
o Predictionist view: argue that only w use of mathematical modeling we can claim
we are taking a scientific approach to reach social phenomena
Trying to identify event regularity and stable functions – predict future –
not helpful approach – provides event regularities
Mathematical modelling used because the math will provide only stable
functions
Predictionist view leads to insistent on mathematical modelling
Why the causal conception of science is more reasonable account of what goes on in
science that predictionist conception:
o Most obvious observation – outside astronomy most of the event regularities
regarded as of interest to natural science are restricted to conditions of well-
controlled experiment
o It’s more/less only in experimental contexts that the predictionist worldview
even appears to hold up – yet successful natural science – hardly restricted to
situations of experimental control
o Even the situation of well-controlled experiment – provides relative support to
Causalist rather than the predictionist account of science
Outside astronomy only time we can be sure of constant conjunctions occurring are in
our experiments:
o Shows us nature of experiment – ensures that irrelevant variables which could
influence outcome are absent
o It’s useful to design/conduct experiments b/c cause equals constant conjunction
only when other things are equal and in nature – other things are never equal –
the natural world is an open system and experiment establishes a closed system
Implications –
o A central aim of the experiment is to understand causal mechanisms not
simply identify event regularities
Real world just not just consist of what we experience or what happens –
it also included the mechanisms that make things happen
, o The importance of tendencies
Tendencies are potentialities which may be exercised or in play w/o being
straightforwardly realized or manifest in any particular outcome
Understanding of causal mechanisms allows us to manipulate/anyway
trigger those mechanisms outside the experiment – where event
regularities typically don’t hold
o Developing our understanding of the nature of science
An essential moment in natural science involves identifying/
understanding causes of phenomena of interest – the practice of
successful event prediction not an essential feature
An understanding of causal mechanisms (ex. Diseases) is what’s typically
required for helping us make world a better place – understanding the
working mechanisms that cause symptoms of illness allow us to intervene
and provide an antidote to the problem
o The Key move in scientific practice
Once Causalist view of science accepted – then it can be recognized that
the essential movement in science –
one whereby drawing on analogies /metaphor we shift from a
conception some phenomena of interest to conception some totally
different type of thing, mechanism structure/condition that is responsible
for given phenomena
It’s a movement paradigmatically from a surface phenomenon to some
deeper causal thing
o Explanatory power v. prediction
Explanatory rather than predictive power must become dominant
criterion of theory adequacy – while objective of assessing reality of the
posited mechanism has to be explicitly acknowledged
Stratification of Nature and Emergence
o If one key aspect to an adequate account of science involves recognising the
existence of real causal mechanisms existing beneath events
o another aspect involves recognising that the natural world is ordered in layers
o idea of layering or stratification of nature is linked to the theory of emergence –
one stratum is emergent from another when it is ontologically dependent on it
but not reducible to it
o emergent stratum has its own laws which cannot be deduced from those of the
stratum from which it is emergent
Change in Scientific Understanding + Change in Material being studied by science
o Further key element to an adequate account of science involves recognizing that
change is possible both at level of our understanding of nature of objects we
study and level of material we study
o No science remains static – scientific theories are continuously changing
o Important to recognize material scientists’ study also not static
