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Study of the self-and all the rest society
Economic Insight
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The World Socio-Economics model is computer model to simulate the consequence of interactions between the earth and human systems based on the World3 model by the work of Club of Rome, The Limits to Growth[1].

The World3 model builds by system dynamics theory that is has an approach to understanding the nonlinear behaviour of complex systems over time using stocks, flows, feedback loops, table functions and time delays.

The Limits to Growth concludes that, without substantial changes in resource consumption, "the most probable result will be a rather sudden and uncontrollable decline in both population and industrial capacity". 

Since the World3 model was originally created, it has had minor tweaks to get to the World3-91 model used in the book Beyond the Limits[2], later improved to get the World3-03 model used in the book Limits to Growth: the 30 year update[3].

References;
[1] Meadows, Donella H., Meadows, Dennis L., Randers, Jørgen., Behrens III, William W (1972). The Limits to Growth. 

[2] Meadows, Donella H., Dennis L. Meadows, Randers, Jørgen., (1992). Beyond the limits: global collapse or a sustainable future.

[3] Meadows, Dennis., Randers, Jørgen., (2004). The limits to growth: the 30-year update.
World Socio-Economics model 2000-2100
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A framework exploring flood risk management in a developing city, under the old paradigm of control - characterised by narrowly defined goals and an over-reliance on hard-engineered structural solutions.
Urban flood risk (control paradigm)
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Circular equations WIP for Runy.

Added several versions of the model. Added a flow to make C increase. Added a factor to be able to change the value 0.5. Older version cloned at IM-46280
Clone of Circularity in Economic models
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This model simulates a COVID outbreak occurring at Burnie, Tasmania. It links the extent to the pandemic with governments intervention policies aiming to limit the spread of the virus. The other part of the model illustrates how will the COVID statistics and the government enforcement jointly influence the economic environment in the community. A number of variables are taken into account, indicating positive or negative relationship in the infection and the economy model respectively.

 

Assumptions

·         Government takes responsive actions when the number of acquired cases exceeds 10.

·         Government’s prompt actions, involving closure of the state border, lockdown within the city, plans on mandatory vaccination and testing, effectively control the infection status.

·         Economic activities are reduced due to stagnation in statewide tourism, closure of brick-and-mortar businesses, and increased unemployment rate, as results of government restrictions.

 

Insights

Government’s rapid intervention can effectively reduce the infected cases. The national vaccination rollout campaign raises vaccination rate in Australians, and particularly influence the death rate in the infection model. Please drag the slider of vaccination to a higher rate and run the model to compare the outcomes.

Although local economy is negatively affected by government restriction policies, consumer demand in online shopping and government support payments neutralize the negative impact on economy and maintain the level of economic activities when infections get controlled. 

Simulation model of COVID outbreak in Burnie Tasmania_Yuchen Zhang_574644
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Socio-Economic Factors
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An initial study of the economics of single use coffee pods.
Helene D. Coffee Pod Investigation
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Marine Tourism Task III - Great Blue Hole
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Social pressures create {Youth Alienation}, leading to youth developing bad behaviours and committing crimes. This attracts {Police Enforcement} who will, in turn, engage the {Community Leadership} where they introduce programs that are designed to assist youth to prevent re-offending through the development of {Community Clubs}, which then contributes to {Community Development}.

{Police Enforcement} collaborates with {Educational Institutions} to boost retention, which translates to socio-economic progress through {Community Development}. On the other hand, criminals are detained and put through the {Court} system, where the offenders are removed from the community through {Imprisonment}. This results in a stable and safe environment, which aid support for {Community Development).

The role of {Community Leadership} in the system, particularly at the grassroots will result is huge savings in the economy, aiding economic growth. The {Community Leadership} collaborates with the {Employment & Justice Agencies}, translating into socio-economic progress {Community Development}

The Community Development Model

This model provides an understanding into the relationships and links between a range of variable units and fixed units, and how {Community Development} is supported.

As {Youth Alienation} rate increases,  the {Crime} rate increases (both variables) demands police enforcement. {Police Enforcement} is a fixed variable as increase in police force is fixed over a period of time. 

To increase efficiency, engages or collaborate with:

•{Community Leadership} (fixed and variable) – is fixed for a certain period, and becomes variable as youth criminal activities increases

•{Court} (variable) – as youth criminal activities increase, the court resources reman fixed. It then removes some offenders from the community and imprison them, creating peace and stability in the community 

•{Educational Institutions} (variables) – as student retention increases, more institutions are needed.  

Variables that are linked to the {Community Leadership} which include;
•{Youth Sports Clubs}
•{Employment & Justice Agencies}
•{Economic Preservation; and}
•{Educational Institutions}

Contribute/support {Community Development}. These are variables, as more youths are referred or engaged.

The {Community Leadership} and {Police Enforcement} collaborate, support and design community programs to reduce youth criminal activities, which could potentially reduce the justice system expenditure.

The relationship between these fixed and variable units create a sustainable Community Development.

The Community Development Model
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SSM Lionfish Management PT2 revised with Storytelling
3 months ago
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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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Justice & Community Support Investment and the Impacts on Bourke Youth Population
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Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon. 

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp (Rutgers University) in support of the SESYNC Climate Learning Project.
Clone of Simple Climate-Carbon-Economic Model
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This model is developed to simulate how Burnie can deal with a new outbreak of COVID-19 considering health and economic outcomes. The time limit of the simulation is 100 days when a stable circumstance is reached. 

Stocks
There are four stocks involved in this model. Susceptible represents the number of people that potentially could be infected. Infected refers to the number of people infected at the moment. Recovered means the number of people that has been cured, but it could turn into susceptible given a specific period of time since the immunity does not seem everlasting. Death case refers to the total number of death since the beginning of outbreak. The sum of these four stocks add up to the initial population of the town.

Variables
There are four variables in grey colour that indicate rates or factors of infection, recovery, death or economic outcomes. They usually cannot be accurately identified until it happen, therefore they can be modified by the user to adjust for a better simulation outcome.

Immunity loss rate seems to be less relevant in this case because it is usually unsure and varies for individuals, therefore it is fixed in this model.

The most interesting variable in green represents the government policy, which in this situation should be shifting the financial resources to medical resources to control infection rate, reduce death rate and increase recovery rate. It is limited from 0 to 0.8 since a government cannot shift all of the resources. Bigger scale means more resources are shifted. The change of government policy will be well reflected in the economic outcome, users are encouraged to adjust it to see the change.

The economic outcome is the variable that roughly reflects the daily income of the whole town, which cannot be accurate but it does indicate the trend.

Assumptions:
The recovery of the infected won't happen until 30 days later since it is usually a long process. And the start of death will be delayed for 14 days considering the characteristic of the virus.
Economic outcome will be affected by the number of infected since the infected cannot normally perform financial activities.
Immunity effect is fixed at 30 days after recovery.

Interesting Insights:
 In this model it is not hard to find that extreme government policy does not result in the best economic outcome, but the values in-between around 0.5 seems to reach the best financial outcome while the health issues are not compromised. That is why usually the government need to balance health and economic according to the circumstance. 
 

New outbreak of COVID-19 in Burnie
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My InsightPublic Opinion Toward Immigration Reform: The Role of Economic Motivations
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Unfolding story based on Emery Roe's 2013 book Making the Most of Mess, revised in 2026. See also Dynamics in Action IM-3239 for more on behavior and The Art of the State IM-11962 for more on Grid-Group Cultural Theory
Managing Mess
4 4 months ago
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Overview

The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.

 

How Does the Model Work?

Both industries can provide economic contribution to Tasmania. Firstly, selling timbers through logging would generate income. Also, spendings from mountain bike riders would generate incomes. However, low tree regrowth rate can not cover up logging, which influences the beautiful vistas and riders' experiences. While satisfaction and expectation depend on vistas and experience, the demand of mountain biking would be influenced through repeat visits and world of mouth as well.

 

Interesting Insights

Although forestry can provide a great amount of economic contribution to Tasmania, over logging goes against ESG framework as well as creating conflict with mountain tourism. As long as the number of rider visits is stable, tourism can always provide a greater economic contribution compared to forestry. Therefore, the government should consider the balance point between two industries.

Simulation of Derby Mountain Bikes versus Forestry
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This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy.

It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10. 

Government intervention - lock down the state, suppress the development of COVID-19 effectively. It is related to most of people stay at home to reduce the exposure in public area.
On the other hand, it also bring the economy of Burnie in the recession, as no tourists, no dining out activities and decrease in money spending in the city.
Clone of Burnie COVID-19 outbreaks and economic impacts_Pui Chu Daisy Cheung 524767
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This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent.

Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely wealth outcomes. Compare buying a home to renting. Note that each run will keep the parameters the same while simulating market volatility.

version 1.8
Home buying simulation 1.8
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Social determinants of health are economic and social conditions that influence the health of people and communities. These conditions are shaped by the amount of money, power, and resources that people have, all of which are influenced by policy choices. Social determinants of health affect factors that are related to health outcomes. Factors related to health outcomes include:
  • How a person develops during the first few years of life (early childhood development)
  • How much education a persons obtains
  • Being able to get and keep a job
  • What kind of work a person does
  • Having food or being able to get food (food security)
  • Having access to health services and the quality of those services
  • Housing status
  • How much money a person earns
  • Discrimination and social support
Determinates of a healthy population
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This model is designed for the local government of Burnie, Tasmania, aiming to help with balancing COIVD-19 and economic impacts during a possible outbreak. 

The model has been developed based upon the SIR model (Susceptible, Infected, Recovered) model used in epidemiology. 

It lists several possible actions that can be taken by the government during a COVID-19 outbreak and provide the economic impact simulation. 

The model allow users to Change the government policies factors (Strength of Policies) and simulate the total economic impact.

Interestingly, the government plicies largely help with controlling the COVID outbreak. However, the stronger the policies are, the larger impact on local economy

Burnie Covid Model, Zilin Huang 533476
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Economic Model
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Model-SIM from Chapter 3 of Wynn Godley and Marc Lavoie's Monetary Economics, adapted for an open economy. The model is stock-flow consistent with only government money--no bills or bonds. No central bank and interest rates do not change. Government spends buying output from the production sector. The production sector is passive turning over all revenue over to households. Households save out of income and spend partially spend out of wealth. Imports and exports pass through the production sector illustrating the idea that consumer households buy from domestic businesses that which they have imported. The model also tracks the sectoral balance flows and changes in equity. Sectoral flows and equity balances match each other dollar for dollar to satisfy the sectoral balances accounting identity (Household Saving - Consumption) + (Business Saving - Expenditure) + (Taxes - Government Spending) - (Exports - Imports) = 0. Since business investment occurs internally to the Business Sector, 
SFC_Model-SIM_open_economy
2 months ago
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Socio-economic