Find Insights | Insight Maker

We start with an SEIR social virality model and adapt it to model social media adoption of Playcast Hosts. *Note that this model does not attempt to model WOM emergent virality.

Social Media Virality3

Alexander St. John

This model depicts the complex relationships between crime, number of police, investment in community development programs and the youth population of the small country town, Bourke.

In this system dynamics model, the user can observe how modifying the spending on community development programs and changing the number of police in the town affects the crime rate and the engagement of youth.

These variables can be altered using the sliders which are provided underneath the notes. The model runs for a period of 5 years. This was deemed the optimal time during which any generational changes could be observed.

The model is explained with more detail below, along with any assumptions and their appropriate reasoning.

Variables

Investment in Community Development Programs

It is assumed that the minimum that can be invested is $1000 and the maximum is $100 000.

Number of Police

It is assumed that the minimum number of police officers that can be present in Bourke is 10 and the maximum is 100.

Stocks and Flows

Bourke Population

The population of Bourke is set as 3000 as stated in the Justice Reinvestment document.

Boredom and lack of opportunity leads to

This flow is given the equation: (50000/[Investment in Community Development Programs])* 2. The greater the investment in community development programs, the lesser the number of youths who are bored.

Disengaged and Alienated Youth

Since there are not many activities for young adults (as stated in the Justice Reinvestment document), it is assumed that they are all currently disengaged and alienated. The disengaged and alienated youth population of Bourke is thus set as 1000 before the model is run.

Petty Crime

Since the youth crime rate for Bourke is quite high, it was assumed that 800 out of the 1000 youth would engage in petty crime. This is before any additions to the police force or increase in community development programs investment.

Commit

This flow is dependent on both the number of disengaged youth and the number of police. The more police that are present in Bourke, the more disengaged the youth become. This ensures that the level of petty crime committed is directly related to the number of police officers.

Convicted

This flow is given a constant rate of 7*[Number of Police] + (0.1*[Petty Crime]). This means that the greater the number of police officers present, the greater the number of convictions. It also means that at the highest number of police officers available (100), the highest the number of convictions is 700 + 10% of youths who commit a crime. Since the model assumes that there are 800 youths committing crime at the beginning of the models’ commencement, it realistically represents the police’s inability to catch ALL criminals.

Not Convicted

This flow has the equation ([Petty Crime]/[Number of Police])*2. Since the number of police is in the denominator, the lower the number, the higher the number of delinquents who are not convicted. This attempts to keep the model realistic. At the maximum level of 100 police officers, there will still remain some delinquents who escape conviction and this remains true to life.

Lesson Learnt

Since youth crime is so rife in Bourke, it is assumed that only 20% of offenders in the juvenile detention centre learn their lesson and never commit crime again. This was done to simplify the modelling.

Still Disenchanted

It is assumed that 80% of offenders do not learn their lesson after their time in the juvenile detention centre.

Feel Estranged

This flow is given the equation: [Number of Police]*5 + 50/([Investment in Community Development Programs]/1000).

Thus, the higher the number of police, the greater the number of youths who feel estranged. The greater the investment in community development programs, the lesser the number of youths who feel estranged.

Participate and engage in

This flow is dependent on the level of investment in community development programs. The greater the investment, the greater the participation. This is realistic as the more money is spent on such programs, the more interested that youths will be in participating.

Develop Inter-community relationships

It is estimated that the majority of youths who participate in community development programs will develop inter-community relationships. This model assumes that such programs will be largely successful in encouraging social harmony amongst the youths.

Relapse

However, youths participating in the community development programs may relapse and head back into the path of crime. However, this is assumed to only be a small minority (1/8 of those who participate).

Interesting Observations

1) Number of Police: 10 (minimum)

Investment in Community Development Programs: $1000 (minimum)

It is important to note that even the minimal amount of investment in community development programs is enough to cause the crime rate to decrease, to the point where, after 3 years, there are more youths who are Reformed and Engaged than those involved in Petty Crime. However, the number of youths who are Reformed decreases after some time, indicating greater investment is needed. Somewhat surprisingly, the number of youths who are involved in the community development programs is at its highest, further suggesting the need for increased investment.

2) Number of Police: 100 (maximum)

Investment in Community Development Programs: $1000 (minimum)

Predictably, Petty Crime has drastically decreased, and in a much shorter time than when there were only 10 police officers. The number of youths who are Reformed and Engaged and those who are involved in the Community Development Programs has also increased, but they are not as high as in the previous observation, most likely due to increased alienation caused by the high police presence.

3) Number of Police: 10 (minimum)

Investment in Community Development Programs: $100 000(maximum)

Quite surprisingly, Petty Crime has decreased drastically, despite the low number of police officers present in Bourke. This shows that the large sums of money being invested in the Community Development Programs has created a social change within the town’s youth population with high numbers of youths participating in these programs and thus becoming Reformed and Engaged. Another interesting aspect is that while the number of youths participating in the programs reduces to zero at the end of the fifth year, the number of youths who are Reformed and Engaged is at an all time high.

4) Number of Police: 100 (maximum)

Investment in Community Development Programs: $100 000 (maximum)

While Petty Crime has decreased significantly, the number of youths who are Reformed and Engaged and those who participate in Community Development Programs is not as high as Scenario 3. Extremely large numbers of youths are also spending time in the Juvenile Detention Centre during the first 2 years of the 5-year model. While repeat offences are low, this may be more due to fear of police brutality and the prospects of harsher sentences than any conscious effort on the youth population’s part to be more harmonious members of society.

Bourke Investment Allocation (Assignment 3)- 44849389

Aheesh Santosh Shetty

Assignment 3 MGMT220
**Scroll down for adjustable sliders**

What is this model?

This model is designed as a simplified field of inputs and outputs for the proposed future justice reinvestment in the north-western NSW town of Bourke. This town is quite small with a total population of around 3,000 people but a worryingly high rate of criminal activity, antisocial behaviour and a generally low sense of community engagement. To plan for a better future this model has been created to map future patterns and changes given certain levels of community investment and policing which can me modified by users, including you!

Key Assumptions & Things to Note:
-Model interactions and consequences only focused on the effects of youth not adults.
-Total youth population assumed to be 1,500 out of the total 3,000 people in Bourke
-Model moves in monthly increments
-Model duration is 5 years (60 Months) as this seems like a realistic time frame for such a project plan to span over
-Engagement return modification allows between 0 and 6 months return to allow insight into the positive effects a shorter engagement time can have on the community
-Police Investment allows adjustment of police force units between 15 and 50
-Community Investment allows an investment of between 0 and 100 to provide a full spectrum of the town with or without investment

Model Prerequisite Understandings:
The model commences with 400 people engaging in criminal activity, and a further 300 people already in juvenile detention to provide a more realistic start point.

Model Analysis:
The most important message this model shows is that there is no one sided solution for everything. Without community investment, regardless of how many police you have the town is still going to be full of bored people committing crimes - just more will be caught and convicted.

On the flip side a town with no police and only community investment may have a low rate of people in juvenile detention and a high number of people in sports teams - but criminal activity may still be higher than optimal due to a low chance of getting caught.

You can see these results for yourselves simply by adjusting the variable sliders on the bottom right of the page to suit your investment interests. Relevant boundaries have been set to give only useful and meaningful information. Furthermore an engagement return tool has been added to show the effects of a slow or fast engagement pickup time ranging from 0 to 6 months. You will note that things change a lot quicker with a shorter engagement return time.

An interesting thing to note is how evenly 3 of the 4 key data fields in the first simulation display (with the outlier being sports team enrolment) when police investment is set to maximum and community investment is set to the minimum - we see essentially an even split between the 3 possibilities: In town, In Juvenile Detention or engaging in Criminal Activity. a 2:1 split of "bad" to "good" things happening. This shows with certainty that just adding policing with no positive reward or outlet for good behaviour results in a flattened cycle of boredom, criminal activity and conviction.

In this model it also seems that Bourke does require a fairly even but high matching of Police and Community Investment. For example setting the policing at 20 and the community engagement higher at say 50 results in indeed a high intake and output of town to sports team memberships however crime rates do still maintain a steady high dictating a more even match between policing and community investment like 40 and 60 to the former and latter to "eradicate" crime. (Of course this will never be 0 in the real world but it is a positive indicator here)

Justice Reinvestment in Bourke | A3 MGMT220 43832512

Alex O'Donnell

Details:

- This model shows the effect of ‘reinvestment program ‘or the expenditure on policing and community development affects the cycles of petty-crime and youth detention, and domestic violence and jail.

More details:

-  Bourke is a town of 3000 people in the North West of New South Wales, about 750Km from Sydney. See the map: https://goo.gl/maps/VgNqgMNzJ7H2. It’s nowhere and there’s not much to do there if you’re young. So, a lot of kids get into mischief, and a lot of adult’s drink. Sometimes they’re violent.

- http://www.justreinvest.org.au/justice-reinvestment-in-bourke/

Assumption:

· Bourke Funding consist of Law enforcement funding and Community Development funding only

o Bourke budget only has $400,000

· Juvenile detention stay last for 6 months

· There is only 2 options as a Youth, commit petty crime or engage in Youth development programs

· 1 unit of Police, Juvenile and Educational program HR and Equipment is = 0.25

o 1 unit increase results in an 0.25 effectiveness increase

· Sport clubs, educational programs and social programs are comprised into Youth Development Program as 1 stock.

· Juvenile support relies on encouraging youth who are in detention centers to join youth development programs, if not they will reoffend.

Stocks:

o Home

o Youth Development program

o Discharged

o Juvenile detention center

o Petty Crime

Variable:

· Reinvestment Allocation – ranges from 0 – 1 , law enforcement investment allocation is 1 – reinvestment allocation. Slide the slider through 0 to 1 to change the reinvestment allocation by 10% l

· Bourke funding budget is fixed to make it seem more realistic (imagine employing a whole army of teachers or police, it wouldn’t make sense)

· Youth Population varies , from 1000 to 10,000 for realism along with its time period (4 years). Slider the the slider to increase or decrease the population by 1,000s

Juvenile support effectiveness rate, Youth development program effectiveness rate, conviction rate, Police HR/ equipment, Juvenile Support HR/ equipment, Youth Development program HR/ equipment

Interrelationship and reinforcing loops

· The youth population starts as as Neutral (Home) then leans towards alienation and connectedness

· Alienation Reinforcing Loop - Alienation has Conviction rate as a factor as conviction rate increase Alienation increase. This is because as youths get arrested, meaning they’ll have to stay in Detention centers, their friends are more likely to follow on due to them getting ‘bored’.

· Connectedness Reinforcing Loop - The opposite exist with Connectedness, as educational program effectiveness increase so as Connectedness. This follows onto the same assumption that youth will always follow peer pressure. The more friends they have in the program, the more likely they will join aswell.

Analysis:

1. Which loop is the youth in?

· Once the allocation slider is used with its minimum or maximum value, the loop at which majority of the youth population is ‘stuck in’ becomes obvious. E.g. Once allocation = 1, the entire youth is stuck between educational program and their home, showing the effectiveness of community development funding. On the other hand, once allocation = 0, the entire youth loops around from doing Petty Crimes, spending their time in Juvenile detention centers, then getting discharged to only commit petty crimes again.

2. Alienation vs. Connectedness

· Set the allocation slider on 0.8, The massive difference between the youth of population feeling connected with their community and youth being alienated can be seen. The increase in Reinvestment, the increase in connectedness. Try the extremes as well, 100% reinvestment funding results in 0 Alienation rate.

3.  What is the Youth Engaged in ? Educational Programs or Petty Crime ?

· Leaving the slider on 0.8, it can be seen that the there are more youth engaged into educational programs than petty crime. This shows that reinvestment and petty crime has a negative relationship .

4. More police = safer ?

- Set the slider on 0.1 , it can be seen that Conviction which has police as a factor is positively correlated to Crime. This means that an increase in conviction rate is equivalent to more youth being alienated and committing crime. Therefore, more police less safer.

Have fun!

44911017_Lorenzo_Casaol_MGMT220

Lorenzo Casaol

Simulation d'un MRU d'un corps qui avance avec une régulation de vitesse réaliste.
Autre version

serie 08a ex4 Une regulation de vitesse plus realiste V2

Bernard2018

Simulation d'un MRU d'un corps qui avance avec une régulation de vitesse réaliste.

serie 08 ex4 Une regulation de vitesse plus realiste V1

lydia tolis

The model simulates the local environmental (specifically greenhouse gas emissions), economic, and resource impacts of transitioning from internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) for personal ownership in New York City in the context of a sustainable program of new energy vehicles, which is the context of the current era. To be realistic, we combine delay and stochasticity in this model to simulate the real world. By understanding the model, one can gain insight into the importance of EV penetration for sustainable development.

SUST 1001U 2024 Fall Group 10 - Electrifying NYC: A System Dynamics Model of EV Adoption and Sustainability Impacts

Xuan Zheng

3

Simple box model for atmospheric and ocean carbon cycle, with surface and deep water, including DIC system, carbonate alkalinity, weathering, O2, and PO4 feedbacks.

LAB #8: Modern Marine 2-box Carbon Cycle

Ashley Morris

5

Flow of successful SBC

Brian J. Gross

The complex systems model ‘Engagement vs Police Expenditure for Justice Reinvestment in Bourke, NSW’ evaluates the effectiveness of allocating government funding to either community engagement activities or law enforcement. In this model, it is possible for the user to designate resources from a scale of 20-100 and to also modify the crime rate for both adults and youth. Below, there are detailed notes that describe the reasoning and assumptions that justify the logic applied to this model. Similar notes can be found when stocks, flows and variables is clicked under the field ‘notes’.

Portions

Government statistics from the Australian Bureau of Statistics (ABS) show that Bourke Shire Regional Council has approximately 3000 residents, made up of 65-63% adults and 35-37% youths.

Crime Rate

Police variable is in the denominator to create a hyperbolic trend. The aim was to achieve a lower crime rate if police expenditure was increased, thus also a higher crime rate if police expenditure was decreased. The figure in the numerator can be changed with the ‘maximum crime rate’ variable which represents the asymptotic crime rate percentage. Where police = 100 the selected crime rate is maximised.

Avoiding Gaol

Originally the formula incorporated the police as a variable, where the total amount of convicted crimes was subtracted from the total amount of crimes committed. However, the constant flow of crimes from repeat offender/a created an unrealistic fluctuation in the simulation. I settled for a constant avoidance rate of 25%. This assumes that an adult or youth committing a crime for the first time is just as likely to avoid conviction as a repeat offender.

Conviction

It is difficult to predict in a mathematical model how many adults or youths are convicted of crimes they commit. I determined a reasonable guess of maximum 75% conviction rate when Police = 100. In this formula, decreasing police spending equates into decreased conviction rate, which is considered a realistic representation.

Released

It is assumed that the average sentence for a youth is approximately 6 months detention. For an adult, it will be assumed that the average sentence is 12 months gaol. The discrepancy is due to a few basic considerations that include 1. Adults are more often involved in serious crime which carries a longer sentence 2. youths are convicted with shorter sentences for the same crime, in the hopes that they will have a higher probability of full rehabilitation.

Engagement

Rate of adult/youth engagement was estimated to be a linear relation. The maximum rate of engagement, assuming expenditure = 100, is set to 80%. This rate of engagement is a reasonable guess with consideration that there will also exist adults who refused to engage in the community and end up in crime, and adults or youth that refuse to engage in the community or crime.

Boredom

Engagement Expenditure variable is in the denominator to create a hyperbolic trend. The aim was to achieve a lower boredom rate with a higher engagement expenditure, and thus a higher boredom rate with a lower engagement expenditure. The figure in the numerator of 25 represents the asymptotic boredom rate percentage, where if engagement expenditure = 100 the adult/youth boredom rate is maximised at 25%.

Assessment #3 Justice Reinvestment in Bourke, NSW 44841396

Mark Robinson

Having ADHD makes life difficult.

There are some types of job that having ADHD makes it extremely difficult to be successful and effective.

Consulting Engineering is one of those.

Being a Consultant Engineer requires mastery of lots of skills - technical skills as well as life skills. The higher levels of rank in the profession requires mastery of more life skills than lower ranks. Having ADHD makes is exceedingly difficult or impossible to master those skills and therefore perform effectively at or above certain levels of rank and responsibility.

ADHD and Consulting Engineering

Dave Davis

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions

Austin Campbell

The model takes into account clothing production and textile waste on a global scale while incorporating Vancouver's own "Fast Fashion" issue into the model.

Please refer to the notes for each variable and stock to see which links were hidden from the model.

Part 2: Our solution for the issue surrounding "Fast Fashion" focuses on increasing individuals education about sustainability and how they can help reduce negative impacts on the environment by shopping less, recycling and donating. This effect of education on sustainability is seen in the "Online Shopping" equation where the impact of "Education on Sustainability" is increased by x1.5 which impacts the entire model. Furthermore, components of the feedback loop on the right are also influenced by increasing education on sustainability and thus, those values were altered accordingly. These values were chosen arbitrarily by taking into account that doubling any value is not realistic so the change should be between x1.0 and x2.0.

Fast Fashion ISCI 360 Solutions Final Edit

V B

739

This version of the CAPABILITY DEMONSTRATION model has been further calibrated (additional calibration phases will occur as better standardized data becomes available). Note that the net causal interactions have been effectively captured in a very scoped and/or simplified format. Relative magnitudes and durations of impact remain in need of further data & adjustment (calibration). In the interests of maintaining steady progress and respecting budget & time constraints, significant simplifying assumptions have been made: assumptions that mitigate both completeness & accuracy of the outputs. This model meets the criteria for a Capability demonstration model, but should not be taken as complete or realistic in terms of specific magnitudes of effect or sufficient build out of causal dynamics. Rather, the model demonstrates the interplay of a minimum set of causal forces on a net student progress construct -- as informed and extrapolated from the non-causal research literature.

Provided further interest and funding, this basic capability model may further de-abstracted and built out to: higher provenance levels -- coupled with increased factorization, rigorous causal inclusion and improved parameterization.

Version 6A: Calibrated Student-Home-Teachers-Classroom

Robert L. Brown

3 3 months ago

plus realiste

mru 4(1)

Daniel Pinto Teixeira

5

The ecosystem of a game park can be made more realistic by introducing financial allocation for active game park quality upgrades, and to reduce the negative results of a high tourist influx. The total amount of money collected is a variable that is dependent on the number of tourists coming to a park until the number levels off at a state of maximum tourist congestion

A model of management decisions with cash reinvestment

Shoeb Hussain

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions

Austin Campbell

Model of the autonomi network economics

autonomi

Christian

Diagrams modified from article

Urban renewal and health inequality

Geoff McDonnell

Peircean process approach to Causation from Menno Hulswit's article. See also Peirce thought insight

Peircean Causation and Causality

Geoff McDonnell

2 months ago

This model demonstrates sustainable recycling and the effects it has on the environment as well as us. We modelled this using realistic statistics and estimates from gridwatch.ca and the Ontario Baseline and Waste & Recycling Report (2023).

[Purple]: Metal demands on a region and the associated environmental and economic factors of production and recycling.

[Pink]: Demand of total residential household and business waste and energy demands on the system.

[Green]: Physical waste produced by human activity in the region.

[Teal]: The outflow of energy produced through waste recycling and its impact of energy production and demand in the region. The Durham-York Energy Center (DYEC) is a facility that combusts garbage into energy which is highlighted in teal, which accumulates with energy produced.

[Orange]: Total energy produced through all means of power generation including modelling of the impact that recycling waste has.

[Yellow]: Carbon emissions of energy generation from energy production methods. (Excluding Wind & Hydro)

Overall, this model examines and compares waste accumulation to energy production and the release of emissions.

scenario 1

Zhuohang Yang

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions

Leah Gillespie

This map is a WIP derived from the MIT D-memo 4641 presentation by Nelson Repenning 1996 and the paper "Nobody Ever Gets Credit for Fixing Problems that Never Happened: Creating and Sustaining Process Improvement" by Nelson P. Repenning and John D Sterman. http://bit.ly/jCXGKL See Insight 9781 for a simulation of this model. This map adds additional features mentioned in the article to the bare bones simulation in IM-9781

The Improvement Paradox Map WIP

Geoff McDonnell

5

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions

Austin Hardesty