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This causal loop diagram illustrates the interconnected factors affecting the economic empowerment of Congolese refugee women in Rwanda, with economic dependency as the central problem reinforced by limited access to vocational training, employment opportunities, and financial services. The diagram shows two key reinforcing loops: one where vocational training leads to employment and income generation, which reduces dependency and improves access to further training (R1), and another where income generation builds self-confidence and skills recognition, leading to better employment opportunities (R2), while language barriers and cultural constraints act as inhibiting factors throughout the system.

Causal Loop Diagram: Economic Empowerment of Congolese refugee women in Rwanda.

Christine

11 months ago

This is the summary of lecture 1 of my Course about StartUps. It's an intro to the startup ecosystem and the different stakeholders that can interact with your new enterprise at different stages of its evolution and growth. -version 1 - for info or suggestions: bonato.pietroz@gmail.com

StartUp ecosystem

PietrOZ

Economic

Carlos Daniel Silva Rosa

Current and proposed Structure of CCP and related Models expanding on the details provided in the Project Completion plan IM-101760

Structure of the CCP Models

Geoff McDonnell

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.

FINAL Clone of Concept Map produced by CCP Workshop 1

Jacqueline Davison

3

An initial study of the economics of single use coffee pods.

Claire - Coffee Pods ISD Humanities v 1.02

Claire Smith

WIP Summary of Mariana Mazzucato's 2018 book See also IM-901 MacroEc

The Value of Everything

Geoff McDonnell

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

Lab 13 Start

Gabe Bowen

232

Despite a mature field of inquiry, frustrated educational policy makers face a crisis characterized by little to no clear research-based guidance and significant budget limitations -- in the face of too often marginal or unexpectedly deleterious achievement impacts. As such, education performance has been acknowledged as a complex system and a general call in the literature for causal models has been sounded. This modeling effort represents a strident first step in the development of an evidence-based causal hypothesis: an hypothesis that captures the widely acknowledged complex interactions and multitude of cited influencing factors. This non-piecemeal, causal, reflection of extant knowledge engages a neuro-cognitive definition of students. Through capture of complex dynamics, it enables comparison of different mixes of interventions to estimate net academic achievement impact for the lifetime of a single cohort of students. Results nominally capture counter-intuitive unintended consequences: consequences that too often render policy interventions effete. Results are indexed on Hattie Effect Sizes, but rely on research identified causal mechanisms for effect propagation. Note that the net causal interactions have been effectively captured in a very scoped and/or simplified format. Relative magnitudes of impact have been roughly adjusted to Hattie Ranking Standards (calibration): a non-causal evidence source. This is a demonstration model and seeks to exemplify content that would be engaged in a full or sufficient model development effort. Budget & time constraints required significant simplifying assumptions. These assumptions mitigate both the completeness & accuracy of the outputs. Features serve to symbolize & illustrate the value and benefits of causal modeling as a performance tool.

Version 9A: Hattie Calibrated Education Scenario Tool Capability Demonstration

Robert L. Brown

23

Based on oid 2016 report to be compared with the Just Justice Framework WIP insight

Overcoming Indigenous Disadvantage

Geoff McDonnell

Deforestation and Economic Development in an Underdeveloped County

Chanaphorn Silaphorn

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy.

Assumptions

The government policy is triggered when number of infected is more than ten.

The government policies will take negative effect into Covid-19 outbreaks and financial system

Parameters

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameters: Infection rate, Background disease, recovery rate.

Adjusted parameter: Immunity loss rate can be change from vaccination rate.

Government policy's parameters

Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters

Fixed parameter: Tourism

Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

Increase vaccination rate and testing rate will decrease the number amount of infected case and a little bit more negative effect to economic system. However economic system still need a long time to recover in both cases.

BMA708_Assignment 3_ndkvo_520272_COVID-19 outbreak and Burnie economy

KV

241004_economic growth model structure_SFD

JF

Economic Model

Brenden Rawls

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.

BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Guy Lakeman

8

Causal loop diagram provided by Gene Bellinger in Projects folder using his AI prompts for Gemini. See also World 2 simulation insight

Limits to Growth (simplified World 3) Causal loop diagram

Geoff McDonnell

2 months ago

Overview:

Overall, this analysis showed a COVID-19 outbreak in Burnie, the government policies to curtail that, and some of the impacts it is having on the Burnie economy.

Variables

The simulation made use of the variables such as; Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate etc.

Assumptions:

From the model, it is apparent that government health policies directly affect the economic output of Burnie. A better health policy has proven to have a better economic condition for Burnie and verse versa.

In the COVID-19 model, some variables are set at fixed rates, including the immunity loss rate, recovery rate, death rate, infection rate, and case impact rate, as this is normally influenced by the individual health conditions and social activities.

Moving forward, we decided to set the recovery rate to 0.7, which is a rate above the immunity loss rate of 0.5, so, the number of susceptible could be diminished over time.

Step 1: Try to set all value variables at their lowest point and then stimulate.

Outcome: the number of those Infected are– 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

Step 2: Try to increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate

Outcome: The number of those Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

With this analysis, it is obvious that the increase of health policy, quarantine, and travel restriction will assist in increase recovery rate, a decrease in confirmed cases, a reduction in death cases or fatality rate, but a decrease in Burnie GDP.

Step 3: Enlarge the Testing Rate to 0.4, variable, others, maintain the same as step 2, and simulate

Outcome: It can be seen that the number of Infected is down to – 152; those recovered down to – 243; overall cases up to – 1022; those that died down to–17,625; while the GDP remains – 824.

In this step, it is apparent that the increase of testing rate will assist to increase the confirmed cases.

Step 4: Try to change the GDP Growth Rate to 0.14, then Tourism Growth Rate to 0.02, others keep the same as step 3, and then simulate the model

Outcome: what happens is that the Infected number – 152 remains the same; Recovered rate– 243 the same; Number of Cases – 1022 (same); Death – 17,625 (same); but the GDP goes up to– 6,632.

This final step made it obvious that the increase of GDP growth rate and tourism growth rate will help to improve the overall GDP performance of Burnie's economy.

The Recent COVID-19 Outbreak in Burnie Tasmania - Buchi Okafor 546792

Buchi Okafor

I made this model to simulate how a companies revenue will change depending on the lifetime of the appliances it manufactures, in combination with the ratio of repair costs and price. It also shows the accumulation of e-waste.

Simulatie apparaten

Henny van Dongen

Economic Effect

Rahmanda Nofal

Laying out and testing before coupling to main model (which is Final Project)

Socio-Economic Factors

Geoffrey Alan Chapman

Implementação do modelo Handy.

Referência:

Motesharrei, S.; Rivas, J.; Kalnay, E. "Human and nature dynamics (HANDY): Modelling inequality and use of resources in the collapse or sustainability of societies". Ecological Economics 101 (2014) 90-102

http://www.sciencedirect.com/science/article/pii/S0921800914000615

HANDY

Daniel Cunha

Crusoe economics test

richardvdlinde

3/24 AISC Draft

lwen2027

3 hours ago

Green lines: positive relationships

Red lines: negative relationships

Spill

Julian Blanc

12 months ago