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 Theory of Structural Change for IAMO Research Group      The part-whole paradigm 

 Examples of
research issues addressed here include the path dependence of farm structures,
regime shifts in land-system change, as well as transitional process
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Theory of Structural Change for IAMO Research Group


The part-whole paradigm

Examples of research issues addressed here include the path dependence of farm structures, regime shifts in land-system change, as well as transitional processes in the evolution of farm structures and innovation systems. All these issues feature counter-intuitive systemic properties that could not have been predicted using standard agricultural economics tools. The key strength of the research group in regard to the part-whole paradigm is the internationally renowned expertise in the agent-based modelling of agricultural policy. (More on what happened here until now / is happening now)

The system-environment paradigm

This paradigm is represented by conceptual research drawing inspiration from Niklas Luhmann’s theory of “complexity-reducing” and “operationally closed” social systems. The attributes of complexity reduction and operational closure are shown to generate sustainability problems, conflicts, social dilemmas, ethical issues, and divergent mental models. The organizing idea explaining these phenomena is the complexity-sustainability trade-off, i.e., the tendency of the operationally closed systems to develop excessive internal complexity that overstrains the carrying capacity of the environment. Until now, the conceptual work along these lines has focused on developing the systems-theoretic principles of ecological degradation and highlighted the sustainability-enhancing role of nonprofit organizations and corporate social responsibility. Another overarching topic has been the analysis of connections between Luhmann’s social systems theory and the evolutionary economics approaches, such as those of Thorstein Veblen and Kenneth Boulding. <!--[if gte mso 9]> Normal 0 false false false DE X-NONE X-NONE <![endif]--><!--[if gte mso 9]> <![endif]--><!--[if gte mso 10]> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-ansi-language:DE;} <![endif]-->
 The L ogistic Map  is a polynomial mapping (equivalently,  recurrence relation ) of  degree 2 , often cited as an archetypal example of how complex,  chaotic  behaviour can arise from very simple  non-linear  dynamical equations. The map was popularized in a seminal 1976 paper by the biologist  Rob

The Logistic Map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often cited as an archetypal example of how complex, chaotic behaviour can arise from very simple non-linear dynamical equations. The map was popularized in a seminal 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation first created by Pierre François Verhulst

Mathematically, the logistic map is written

where:

 is a number between zero and one, and represents the ratio of existing population to the maximum possible population at year n, and hence x0 represents the initial ratio of population to max. population (at year 0)r is a positive number, and represents a combined rate for reproduction and starvation.
For approximate Continuous Behavior set 'R Base' to a small number like 0.125To generate a bifurcation diagram, set 'r base' to 2 and 'r ramp' to 1
To demonstrate sensitivity to initial conditions, try two runs with 'r base' set to 3 and 'Initial X' of 0.5 and 0.501, then look at first ~20 time steps

 This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .  And EBOLA

This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .

And EBOLA


Simulation of MTBF with controls   F(t) = 1 - e ^ -λt   Where    • F(t) is the probability of failure    • λ is the failure rate in 1/time unit (1/h, for example)   • t is the observed service life (h, for example)  The inverse curve is the trust time On the right the increase in failures brings its
Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
    Model Explanation:   This system dynamics model visualises the impact on investment into policing and community engagement resources on the crime rates within the youth population of Bourke, NSW.  The model also adds in the variable of funding for safe houses. With a high rate of domestic violen

Model Explanation:

This system dynamics model visualises the impact on investment into policing and community engagement resources on the crime rates within the youth population of Bourke, NSW. 
The model also adds in the variable of funding for safe houses. With a high rate of domestic violence, unfavorable home conditions and other socio-economic factors, many youth roam the streets with no safe place to go, which may lead to negative behaviour patterns.


Assumptions

Youth Population: 700
Total youth population in 2016 for Bourke LGA was 646 (ages 10-29). (Census, 2016) Figures rounded to 700 for purposes of this model simulation. 

Constants:
70% registration and engagement rates for Community funded programs
30% attendance rate for Safe Houses
50% crime conviction rate


Variables

Positive and Negative Influences

The model shows a number of key variables that lead youth to become more vunerable to commit a crime (such as alienation, coming from households with domestic violence, boredom and socio-economic disadvantages such as low income), as well as the variables that enhance the youth's likelihood to be a contributing member of the community (developing trusted relationships and connections with others, and having a sense of self worth, purpose and pride in the community). These factors (positive and negative) are aggregated to a single rate of 50% each for the purposes of the simulation, however each individual situation would be unique.  

Police Funding / Resources

Police funding and resources means the number of active police officers attending to criminal activities, as well as prevention tactics and education programs to reduce negative behaviour. The slider can be moved to increase or decrease policing levels to view the impact on conviction rates. Current policing levels are approx 40 police to a population of under 3000 in Bourke.

Crime Rate

Youth crime rates in Australia were 3.33% (2016). Acknowledging Bourke crime rates are much higher than average, a crime rate of 40% is set initially for this model, but can be varied using the sliders. 


Community Program Funding / Resources

Community Program Funding and Resources means money, facilities and people to develop and support the running of programs such as enhancing employability through mentorship and training, recreational sports and clubs, and volunteering opportunities to give back to the community. As engagement levels in the community programs increase, the levels of crime decrease. The slider can be moved to increase or decrease funding levels to view the impact on youth registrations into the community programs.

Observations

Ideally the simulations should show that an increase in police funding reduces crime rates over time, allowing for more youth committing crimes to be convicted and subsequently rehabilitated, therefore decreasing the overall levels of youth at risk.

A portion of those youth still at risk will move to the youth not at risk category through increased funding of safe houses (allowing a space for them to get out of the negative behaviour loop and away), whom them may consider registering into the community engagement programs. An increase in funding in community engagement programs will see more youth become more constructive members of the community, and that may in turn encourage youth at risk to seek out these programs as well by way of social and sub-cultural influences.

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 Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

From Schluter et al 2017  article  A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017  video .   See also Balke and Gilbert 2014 JASSS  article  How do agents make decisions? (recommended by Kurt Kreuger U of S)
From Schluter et al 2017 article A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017 video. See also Balke and Gilbert 2014 JASSS article How do agents make decisions? (recommended by Kurt Kreuger U of S)
A government deficit means that more money has been transferred in the form of payments or investments from the government sector to the private sector than the government has received in taxes. As shown in the drawing,  GOVERNMENT DEFICIT = INCOME AND SAVING for the private sector. Not all the inco
A government deficit means that more money has been transferred in the form of payments or investments from the government sector to the private sector than the government has received in taxes. As shown in the drawing,  GOVERNMENT DEFICIT = INCOME AND SAVING for the private sector. Not all the income transferred from the government to the private sector will be employed and some of it will be saved in bank accounts. It is therefore correct to say that Government Deficits lead to Private Sector Saving. It is equally true to say that Investment  leads to Saving. This is important because in the current recession one of the major problems is the massive amount of private debt. In these circumstances a cumulative government deficit is necessary to help the private sector save and repay some of its debt. Note: I have not taken into account the foreign sector here which can also contribute to private sector income and saving.
COVID-19 Outbreak in Burnie Tasmania Simulation Model    Introduction:     This model simulates the COVID-19 outbreak situation in Burnie and how the government responses impact local economy. The COVID-19 pandemic spread is influenced by several factors including infection rate, recovery rate, deat
COVID-19 Outbreak in Burnie Tasmania Simulation Model

Introduction:

This model simulates the COVID-19 outbreak situation in Burnie and how the government responses impact local economy. The COVID-19 pandemic spread is influenced by several factors including infection rate, recovery rate, death rate and government's intervention policies.Government's policies reduce the infection spread and also impact economic activities in Burnie, especially its tourism and local businesses.   

Assumptions: 

- This model was built based on different rates, including infection rate, recovery rate, death rate, testing rate and economic growth rate. There can be difference between 
this model and reality.

- This model considers tourism and local business are the main industries influencing local economy in Burnie.

- Government's intervention policies will positive influence on local COVID-19 spread but also negative impact on local economic activity.

- When there are more than 10 COVID-19 cases confirmed, the government policies will be triggered, which will brings effects both restricting the virus spread and reducing local economic growth.

- Greater COVID-19 cases will negatively influence local economic activities.

Interesting Insights:

Government's vaccination policy will make a important difference on restricting the infection spread. When vaccination rate increase, the number of deaths, infected people and susceptible people all decrease. This may show the importance of the role of government's vaccination policy.

When confirmed cases is more than 10, government's intervention policies are effective on reducing the infections, meanwhile local economic activities will be reduced.

How education causes the gap between socio-economic status?
How education causes the gap between socio-economic status?
Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017.     Current premier version containing Story Steps and text for vincy to update. This is clone of 97129 via Vincy.
Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017. 

Current premier version containing Story Steps and text for vincy to update.
This is clone of 97129 via Vincy.
Extremely basic stock-flow diagram of compound interest with table and graph output in interest and savings development per year. Initial deposit, interest rate, yearly deposit and withdrawal can all be modified in Dutch.
Extremely basic stock-flow diagram of compound interest with table and graph output in interest and savings development per year. Initial deposit, interest rate, yearly deposit and withdrawal can all be modified in Dutch.