Wow! Having found myself attending Chuks Okereke's class on climate and justice this term at Oxford, my head is not only swimming, but I'm about to take a jump off the deep end ... pause for awkward silence.
Is it posible to achieve justice in the presence of complexity? And I don't just mean the multifaceted nature of the concept (rather than conception :-) itself, but that when we talk of the implementation of justice within complex systems, it no longer seems ascertainable. This is because not only is justice a complex issue in and of itself, but to which part of the system are we referring when we say we want it to be just and equitable. Justice implies trade-offs and compromise, but with a complex system one never fully has a grasp of the whole picture: of what the possible feedbacks could be, what the knock-on effects are and whether this will actually result in a less just system. In order for there to be justice within a system, that system needs to be defined: this is a political process in itself and loaded with areas for exclusion of relevant stakeholders. Can a system ever be 'just' if at the stage at which it is defined we cannot hope ever to achieve full participation?
We can, of course, make vast improvements in our level of inclusion at the decision-making stage, at being reflexive of our own preconceived notions and ideologies that are framed by our backgrounds (both disciplinary and others), but is this sufficient? On the other hand, throwing our hands up in despair at the complexity of it all is also not particularly helpful and it could be argued that it reinvigorates the inequality f no-one is standing up to it. (This post has now been severely reconfigured in light of Ariella Helfgott's class on system theory and resilience so apologies for the conflation and confusion of ideas :-).
I clearly don't have the answers, but I just wanted to throw it out there as a problematic to which I may later return. It brings up issues of how to deal adequately with uncertainty and complexity- not to ignore them nor to try to minimise or eliminate them, but to incorporate them in our system governance, which includes the loaded notions like justice.
Until then- my head is stuck in another random post so I will return to this question at a later stage!
L
xxx
Sunday, 14 November 2010
Practising complexity: the ecological vs industrial food system
Warning: this is going to sound like a greenie-lefty, anti-western/capitalist rant, which it probably is, but then maybe that's what it's meant to be :-)
This post sparked from reading chapter 11 of Michael Pollan's 2006 book- The omnivore's dilemma and it is summarised in a quote from page 214: that in contrast to the efficiencies reached in the industrial system through simplification, "the efficiences of natural systems flow from complexity and interdependence." The general thrust of his argument is one in favour of grass-fed 'ecological' systems that focus on the local versus the industrialised, corn-fed conveyer belt systems from which most food (especially in the US) is derived.
The latter seems to be more complex as it is global and involves multiple inputs not only of chemical pesticides and synthetic fertilisers, but of antibiotics and organisms bred for particular traits (such as an ability to convert obscene amounts of corn into lots of protein or to grow large and erect stems in order to pack more plants per row and make harvesting easier. This monoculture of sub-species clearly has a big impact on diversity- one of the foundations of an ecologically resilient system). Local, 'traditional' farming methods seem to be almost quaint in their simplicity and yet when one actually starts to get to grips with the systems themselves a different picture emerges. The industrial food complex has become a mechanised linear system with fertilisers, pesticides, antibiotics seeds and animals going in on one end and supermarket food coming out the other side after various levels of processing in between----> the ubiquitous, fossil-fuel- dependent black box. There is no element of agency from anything other than the powers that control the process: soil is kept fertile by adding fertiliser, monocultures are protected through herbicides and plants' natural defences are made redundant through pesticides- animals are merely protein-making factories fed corn and expected to produce beef steaks and because this is not necessarily their diet of choice (they are ruminants after all and a rumen's chief function is for digesting grass, not corn) their illnesses are kept at bay by the use of antibiotics. the same can be argued for chickens, pigs, sheep and other protein converters- even fish are now being fed corn!!! The complexity of this system stems less from the system itself, than the covert black box through which it operates which is phenomenally closed to the average consumer who is merely confronted with the end product in a supermarket. Even fresh produce (and some organic products- see the book for more on this) goes through a similar process where every step in the chain is controlled and individual agency is brought in line with the needs and requirements of the system.
On the other hand, we have the pastoral idyll that is conjured up in our imaginations when we think of the farm. Open grasslands, grazing cattle, chickens running around the farmyard etc etc etc... so simple, and yet when the underlying processes are reveled- it is shrouded in the complexity inherent in any ecologically based system (I don't like to use the value-laden adjective 'natural'). Soil is not just soil, but a combination of earth, roots, manure, decaying matter, earthworms and bacteria converting this matter into its constituent elements for uptake into the above-ground system. Grass is not just grass-it comprises multiple species (including nitrogen-fixing clovers and leguminous species) with varying nutritional values, tastes and growth patterns. Grazers like cows and sheep are as fussy about their grasses as you and I are about our dinner. Chickens thrive off the larvae etc that colonise cow pats and thus keep the system healthy- pigs are the best manure producers... happy as a pig in shit is no misnomer. Any tweak in any part of this system will have repercussions in the rest of the system and yet it is dynamic- an ongoing process of feedback loops all fed by solar energy converted through photosynthesis, land and water. Yes, I have painted a very pretty picture of the traditional farm, but you get my point- nothing linear, all is interdependent and because of this it is not static, but dynamic- less easy to control, but it is inherently self-organisational and manages itself quite well as a socio-ecological system. You are not constantly playing catch-up with 'nature' as in the industrial machine where all externalities are eliminated through pesticides, anti-biotics, sterilisation- even cutting off pigs' tail so they don't suckle them in lieu of their mothers... the definition of 'unsustainable'?
Complex systems versus complex food
Rather we are more likely dealing with simple systems resulting in complex food (containing more random names of substances that I only barely recall from first year undergrad chemistry), and complex systems resulting in pretty simple food. Perhaps instead of fighting the complexity of the system, we should engage with it instead of trying to make it malleable to our needs as this is likely to end up in a constant game of catch-up which we are unlikely to win because agency cannot be managed into constituent components. The question is why we turned to this industrial system in the first place? The first argument would be that it is required to feed a growing population- partially true, but to feed a growing population what exactly- an over-abundance of corn converted into a myriad of other corn-based products? In the developed world, an under-production of food cannot possibly be the rationale... so I take the more cynical view of keeping the great industrial giant alive and kicking- and then exporting this system to places that never thought of food in this way before so that they feel the need that in order to produce sufficient food, they need their own supply of inputs- and thus become dependent upon the providing hand of the West, not just for these manufactured inputs, but for plants and seeds themselves- the production of which should surely be left to the plants themselves??? (I'm not actually against GMOs per say, but don't get me started on the IP-based rationale behind terminator technology, grrrrrr!)
Urban systems of food consumption
However, as much as this return to the rural idyll is all very good and well (for those like Joel Salatin, the farmer whose farm forms the basis of Michael's chapter and the above rant), how realistic is it within the increasingly urbanised world in which we live where very few of us would know what to do with a cow if confronted with one (alive and not hanging from a peg in a butcher or even better, packaged into steaks/chops/mince... in local supermarket's fridge)... although cycling through the meadow at Oxford I have confronted a few, but that is another story for another time :-)
Is this sun/water/grass-fed system sustainable if it needs to feed not only the local community, but the megalopolis of 15 million people at the other end of the road/country/region/continent/world? In countries like NZ, South Africa, Argentina and even Brazil- it can be argued that yes, this is do-able. Local sourcing of most products occurs within the borders of the country and there is sufficient space etc etc and a national mentality that still allows for this type of farming (although perhaps not consciously), but it is increasingly under threat by the draw of the non-seasonality of food, TV dinners and pre-prepared food culture that dominates in world where people barely have the time to make a sandwich let alone cook a full three-course nutritious meal once a day.
Blame has at times been laid at the feminist movement- that now that women are working, they are no longer shackled to the kitchen stove cooking food for their families 24/7 and must now rely on the convenience brought by the industrial food system. Would a return to the traditional complex farm mean a return to the good ol' days of mom's home cooked meal? Or can it be a progressive step forward where we don't just question where our food comes from and what we are actually eating, but the entire lifestyle in which we consume food-on the go in our cars or a meal around the dinner table that everyone has chipped in to prepare?
Re-thinking our food system, not only requires re-conceptualising what we what to eat, but how we want to eat it- namely our lifestyles and what repercussions on the world we are prepared to live with in order to get our coffee fix every morning. We can no longer claim ignorance of the black box as consumers, but we need to pull it apart and define what we find acceptable and what needs fundamental change.
Although I clearly have more to say on the matter, I'm going to leave it there
Food for thought...
-L
This post sparked from reading chapter 11 of Michael Pollan's 2006 book- The omnivore's dilemma and it is summarised in a quote from page 214: that in contrast to the efficiencies reached in the industrial system through simplification, "the efficiences of natural systems flow from complexity and interdependence." The general thrust of his argument is one in favour of grass-fed 'ecological' systems that focus on the local versus the industrialised, corn-fed conveyer belt systems from which most food (especially in the US) is derived.
The latter seems to be more complex as it is global and involves multiple inputs not only of chemical pesticides and synthetic fertilisers, but of antibiotics and organisms bred for particular traits (such as an ability to convert obscene amounts of corn into lots of protein or to grow large and erect stems in order to pack more plants per row and make harvesting easier. This monoculture of sub-species clearly has a big impact on diversity- one of the foundations of an ecologically resilient system). Local, 'traditional' farming methods seem to be almost quaint in their simplicity and yet when one actually starts to get to grips with the systems themselves a different picture emerges. The industrial food complex has become a mechanised linear system with fertilisers, pesticides, antibiotics seeds and animals going in on one end and supermarket food coming out the other side after various levels of processing in between----> the ubiquitous, fossil-fuel- dependent black box. There is no element of agency from anything other than the powers that control the process: soil is kept fertile by adding fertiliser, monocultures are protected through herbicides and plants' natural defences are made redundant through pesticides- animals are merely protein-making factories fed corn and expected to produce beef steaks and because this is not necessarily their diet of choice (they are ruminants after all and a rumen's chief function is for digesting grass, not corn) their illnesses are kept at bay by the use of antibiotics. the same can be argued for chickens, pigs, sheep and other protein converters- even fish are now being fed corn!!! The complexity of this system stems less from the system itself, than the covert black box through which it operates which is phenomenally closed to the average consumer who is merely confronted with the end product in a supermarket. Even fresh produce (and some organic products- see the book for more on this) goes through a similar process where every step in the chain is controlled and individual agency is brought in line with the needs and requirements of the system.
On the other hand, we have the pastoral idyll that is conjured up in our imaginations when we think of the farm. Open grasslands, grazing cattle, chickens running around the farmyard etc etc etc... so simple, and yet when the underlying processes are reveled- it is shrouded in the complexity inherent in any ecologically based system (I don't like to use the value-laden adjective 'natural'). Soil is not just soil, but a combination of earth, roots, manure, decaying matter, earthworms and bacteria converting this matter into its constituent elements for uptake into the above-ground system. Grass is not just grass-it comprises multiple species (including nitrogen-fixing clovers and leguminous species) with varying nutritional values, tastes and growth patterns. Grazers like cows and sheep are as fussy about their grasses as you and I are about our dinner. Chickens thrive off the larvae etc that colonise cow pats and thus keep the system healthy- pigs are the best manure producers... happy as a pig in shit is no misnomer. Any tweak in any part of this system will have repercussions in the rest of the system and yet it is dynamic- an ongoing process of feedback loops all fed by solar energy converted through photosynthesis, land and water. Yes, I have painted a very pretty picture of the traditional farm, but you get my point- nothing linear, all is interdependent and because of this it is not static, but dynamic- less easy to control, but it is inherently self-organisational and manages itself quite well as a socio-ecological system. You are not constantly playing catch-up with 'nature' as in the industrial machine where all externalities are eliminated through pesticides, anti-biotics, sterilisation- even cutting off pigs' tail so they don't suckle them in lieu of their mothers... the definition of 'unsustainable'?
Complex systems versus complex food
Rather we are more likely dealing with simple systems resulting in complex food (containing more random names of substances that I only barely recall from first year undergrad chemistry), and complex systems resulting in pretty simple food. Perhaps instead of fighting the complexity of the system, we should engage with it instead of trying to make it malleable to our needs as this is likely to end up in a constant game of catch-up which we are unlikely to win because agency cannot be managed into constituent components. The question is why we turned to this industrial system in the first place? The first argument would be that it is required to feed a growing population- partially true, but to feed a growing population what exactly- an over-abundance of corn converted into a myriad of other corn-based products? In the developed world, an under-production of food cannot possibly be the rationale... so I take the more cynical view of keeping the great industrial giant alive and kicking- and then exporting this system to places that never thought of food in this way before so that they feel the need that in order to produce sufficient food, they need their own supply of inputs- and thus become dependent upon the providing hand of the West, not just for these manufactured inputs, but for plants and seeds themselves- the production of which should surely be left to the plants themselves??? (I'm not actually against GMOs per say, but don't get me started on the IP-based rationale behind terminator technology, grrrrrr!)
Urban systems of food consumption
However, as much as this return to the rural idyll is all very good and well (for those like Joel Salatin, the farmer whose farm forms the basis of Michael's chapter and the above rant), how realistic is it within the increasingly urbanised world in which we live where very few of us would know what to do with a cow if confronted with one (alive and not hanging from a peg in a butcher or even better, packaged into steaks/chops/mince... in local supermarket's fridge)... although cycling through the meadow at Oxford I have confronted a few, but that is another story for another time :-)
Is this sun/water/grass-fed system sustainable if it needs to feed not only the local community, but the megalopolis of 15 million people at the other end of the road/country/region/continent/world? In countries like NZ, South Africa, Argentina and even Brazil- it can be argued that yes, this is do-able. Local sourcing of most products occurs within the borders of the country and there is sufficient space etc etc and a national mentality that still allows for this type of farming (although perhaps not consciously), but it is increasingly under threat by the draw of the non-seasonality of food, TV dinners and pre-prepared food culture that dominates in world where people barely have the time to make a sandwich let alone cook a full three-course nutritious meal once a day.
Blame has at times been laid at the feminist movement- that now that women are working, they are no longer shackled to the kitchen stove cooking food for their families 24/7 and must now rely on the convenience brought by the industrial food system. Would a return to the traditional complex farm mean a return to the good ol' days of mom's home cooked meal? Or can it be a progressive step forward where we don't just question where our food comes from and what we are actually eating, but the entire lifestyle in which we consume food-on the go in our cars or a meal around the dinner table that everyone has chipped in to prepare?
Re-thinking our food system, not only requires re-conceptualising what we what to eat, but how we want to eat it- namely our lifestyles and what repercussions on the world we are prepared to live with in order to get our coffee fix every morning. We can no longer claim ignorance of the black box as consumers, but we need to pull it apart and define what we find acceptable and what needs fundamental change.
Although I clearly have more to say on the matter, I'm going to leave it there
Food for thought...
-L
Wednesday, 21 April 2010
Complexity Economics 1
Before I even attempt to get started on this in my non-economist naïveté, just to give you a list of the sources that I have consulted so far in order to start piecing together this elusive subject:
The Economy as an Evolving Complex System III (2006) Eds Lawrence E Blume & Steven N Durlauf, OUP
The Origin of Wealth (2006) Eric D, Beinhocker, HBS and his talk at the Smith School, posted here: http://www.smithschool.ox.ac.uk/economics-and-public-policy-2/
Podcasts from the James Martin 21st Century school: Prof Geoffrey West, Santa Fe Institute, available from podcasts.ox.ac.uk
Beinhocker refers to complexity economics as paradigm shifting: i.e. not a 'how to do' but a 'how to think.' Starting from this premise, he then proceeds to outline the history of economics as a discipline, reliant on physics for its initial mathematical development. Unfortunately as physics developed in line with our better understanding of the physical environment and processes that occur across scales and made assumptions accordingly, economics failed to remould the assumptions upon which it was formulated. These 'laws' then became as ingrained as Newton's and Einstein's laws of physics, yet the fundamental principle of system equilibrium upon which they are based failed to take into account the 2nd law of thermodynamics (the tendency to entropy (disorder) in isolated systems). The assumption that the economic system is a closed system tending to equilibrium underpins key problematic laws in economics. Those relevant to my work on the food system include: the law of supply and demand driving towards market equilibrium price despite the evident existence of stocks, backlogs, time lags etc... and the law of 1 price where in the absence of transport costs and trade barriers, identical products must sell at the same price in all markets, which is very problematic when not using aggregate data (i.e. looking at the local level/fine-grained analysis). (Beinhocker notes that the more interesting question is actually that of price convergence and dynamic interplay over time between incentives for decision making and the changing nature of various barriers.
Beinhocker refers to complexity economics as paradigm shifting: i.e. not a 'how to do' but a 'how to think.' Starting from this premise, he then proceeds to outline the history of economics as a discipline, reliant on physics for its initial mathematical development. Unfortunately as physics developed in line with our better understanding of the physical environment and processes that occur across scales and made assumptions accordingly, economics failed to remould the assumptions upon which it was formulated. These 'laws' then became as ingrained as Newton's and Einstein's laws of physics, yet the fundamental principle of system equilibrium upon which they are based failed to take into account the 2nd law of thermodynamics (the tendency to entropy (disorder) in isolated systems). The assumption that the economic system is a closed system tending to equilibrium underpins key problematic laws in economics. Those relevant to my work on the food system include: the law of supply and demand driving towards market equilibrium price despite the evident existence of stocks, backlogs, time lags etc... and the law of 1 price where in the absence of transport costs and trade barriers, identical products must sell at the same price in all markets, which is very problematic when not using aggregate data (i.e. looking at the local level/fine-grained analysis). (Beinhocker notes that the more interesting question is actually that of price convergence and dynamic interplay over time between incentives for decision making and the changing nature of various barriers.
An interesting footnote is that he calculates that if the economic system were tending to equilibrium, this would take approximately 4.5X10 to the 18 (a few quintillion) years, makes you think, wot)
Furthermore, this fixation on equilibrium has resulted in various other problematic assumptions including rationality, perfect information and treating endogenous factors as external to the system. Rather, by relaxing some of these to include dynamism and less than perfect information/rationality/markets, the explanatory value of economics can be harnessed (rather than its predictive ability which is shaky at best and which is actually only 1/2 of the usefulness of models). By testing hypotheses based on what we see- i.e. with actual data that is not aggregated- the explanatory power of certain models can be tested in a scientifically rigorous way. Obviously the critical aspect of this is to collect the requisite data in the first place and to start testing theories rather than just statistical correlation (á la econometrics) which does not lead to conclusions of causation.
Complexity economics is therefore not the antithesis of neoclassical economics, but rather a re-evaluation of the mathematical principles upon which economics is based in order to bring them in line with current knowledge through the sciences on systems in general. By being able to analyse the economic system (a social system) in a manner similar to that in which natural systems are studied is the first step in being abe to research socio-ecological systems like the food system. Points from complexity science to bear in mind when trying to bridge this divide:
Complexity is scale dependent (We know the equations governing the solar system, yet it is extremely difficult to model a forest ecosystem in its entirety)
Networks recur at all levels across all systems: E.g. neural networks, business organisations, economies, trading regimes, social/community networks...
So, I'll leave you chew over that for now- I promise a part 2 (and maybe 3, 4... to follow :-)
L
Friday, 29 January 2010
Part 5: On the futility of models
I write this as I am sitting in the hotel lobby of the Hotel Cardoso in Maputo, trying to recover from a manic week of seemingly never-ending interviews, traffic jams, gate-crashing (of international conferences and cocktail parties) and run-ins with the police. One more interview to go, I lack the energy to work on anything substantive to do with my PhD although I know that I will have to face the inevitable at some point and actually come up with something concrete, even of it is just for the presentation I have been asked to give At Ed Mondlane university on my return to Mozambique or to prepare for adding an extra trip to Zambia to consult with the contacts I have made there, but the real stress and concern sitting on my shoulders at the moment is that of my newly adopted supervisor whose comments and suggestions I need to try and incorporate into a coherent critique of or even a novel type of climatico-economic model.
And so, please find below my thoughts on models as I attempt to answer the questions posed to me...
Why do we need models?
Do we? This question should really be based more on answering the next question...
What do we do with models?
Are they explicative or predictive or merely self-indulgent? Do they make us answer questions with more questions are are they actually useful in leading us down a thought path from which we may alight more enlightened further down the track? What is their function... to understand more about how the world works, to explain things we can't actually manipulate ourselves, to predict the future or simply to see how things could possible work if the world happened to function in this particular way whether it be linearly, non-linearly, stochastically or whatever, only then will we be able to answer the first question. But, do we really know?
Can we argue all of the above? In terms of policy, surely they should be predictive- we can't make decisions based on theory, there needs to be a probability of occurrence, but this probability is calculated based on the representivity of the model to the real world and hence the likelihood of the predicted outcome occurring (taking into account all the stats of how much the model is actually reflected in reality through models of collected data (the real situation... or merely the quantitative aspect of the real situation- here the problem between modelling physical processes and others becomes a tad shifty)
So I digress...
Leaving this for a second, I turn to what types of models we may employ for these carious
What type of models are we then talking about?
Models as thought-experiments can be extremely useful to the individual researcher, even if just to distract him with mathematical relationships that may not necessarily happen in reality, but which are nevertheless interesting building blocks for future research. E.g.s include many ecological models which stick to the general and don't pretend to be examples of reality. Rather they look at relationships between things and processes such as predator-prey models or source-sink population models that include stochastic variables.
Will inductive models that are based on relationships between empirical data and which are then made into general principles (and the deductive approach of taking general principles and matching them to specific situations for that matter) ever get us anywhere because anything that you're bothering to model in the first place is not going to slip nicely into a generic mathematical formula (will it... the more we know the less we know we know, right?) We live shrouded in complexity- the real question is whether down/upscaling processes through dis/aggregating data is actually a true reflection of the world... is the world really one big fractal? Thrift in his non-representational theory bent will argue most definitely not... representations/reflections... models for that matter are all nonsense.
Well, yes, they may be nonsense, but are they useful?
Can models ever be predictive or are they simply projections, handled under varying scenarios... (read here IPCC/Millennium ecosystem assessment scenarios par example)
However, due to the need to give them more credence than their due for making policy based decisions, these models have been accorded higher value than the initial intent of their modellers... take climate change controversy or climategate!!! Yes, the models are not 100% certain- scientists never function in a world of certainty, but the indications are definitely there and the general trends can be modellef pretty successfully, especially if most of the uncertainty points towards worse results than those projected (NOT predicted) by incorporating non-linear relationships and positive feedbacks (ice-caps melting and albedo effect)
BUT when adding in socio-economic factors are we not straying a bit too far into the unknown. We can't predict a future of climate change, but the likelihood that we are heading in that direction is extremely strong based on data collected and events we can already see, but socio-economic models of the current situation are fraught with problems when scaled up because unlike the climate, socio-economic factors are location and context specific and although they have global impacts, they do not work in a similar way to the global climate system. Hence combining the two is extremely difficult, especially when as much credence is given to the model of food security outcomes under climate change (for example) which are modelled on scenarios and take a macro-view of a globally extremely differentiated situation (all conceded by the authors of course because they know they are dealing with the unknown). In order to improve this, we need local level data- it's no good working with international food prices if someone in rural Mozambique is paying far higher prices (or even proportional to their income far higher) for their maize than your average Joe Soap in the USA.
Therefore...
What data is required?
For global studies? LOTS!!!... and a supercomputer to compute it
Rather, instead of predictive/projection models we should be focussing on modelling subsystems that we know a bit more about and for which we have available data at whatever level is required in order to see how certain processes work... but then to stop there and not to draw inferences from one situation into general principles because there will always be a snag. Rather, admit that what is studied is not 100% explicative or predictive, but can lead to assessments of different situations based on the knowledge of a specific example and experimentation.
Not what your average politician wants to hear about certainty, but at least probably more useful
Proviso: please note that my views expressed above are the work of an over-tired mind at ends with trying to come to terms with models and that I will most likely change my mind about their utility tomorrow- this is not aimed to criticise the modelling community, but more of a critique of how we apply the knowledge gained from said activity and how our expectations of what models can offer us (in the practitioner community) often far outweigh what modellers know they can do
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