Opportunity Details

Help us tidy up a property under development. Lots of yard work, painting, removeal of old carpet. Come lend some sweat equity!

Opportunity Details

Wildfire Prevention environmental science knowledge analyst, CrowdDoing

Prevention derivatives is driven by the thesis that there is an under-valuation of passive risk (or the cost of inaction) and an under-prioritization of positive risk. Correspondingly for wildfires as an example, there is an under-recognition of the potential shared value upside of preventative action through social innovation and social interventions (such as goats & sheep that prevent wildfires). CrowdDoing.world's aim is to guarantee positive risk through leveraging existing liabilities to allow for the implications of prescriptive analytics to be financed. The under-pricing of passive risk means that liabilities are treated as either costs of doing business or un-predictable risks even for entirely preventable risks. Risk management offices have been too biased towards avoiding taking the wrong risks rather than ensuring that institutions make their own luck by seizing the abundant positive risk opportunities in social innovation. Meanwhile, the bias against positive risk leaves social innovations not to get adopted even if there would be remarkable benefits to all stakeholders if they were adopted

Wildfire Prevention environmental science knowledge analyst, CrowdDoing

1. Identify and collect data relevant to assigned project (e.g., Forest Fire Prevention, Biophelia in Hospitals, Crypto Impact Potential)
2. Establish costs incurred by target stakeholders as a result of select threat(s) (e.g., wildfire)
3. Develop recommended solutions based on analysis, cite resources
4. Present findings.
https://drive.google.com/file/d/1jx3iv8LETHC2MaAS7bSY_XScup0aTVXk/view?usp=sharing

If you have any questions about processes for joining CrowdDoing.world as a volunteer to support our efforts in systemic change please write to volunteerorientation@crowddoing.world

Opportunity Details

Wildfire Prevention Financing Data Analyst- CrowdDoing Volunteer
-Prevention derivatives is driven by the thesis that there is an under-valuation of passive risk (or the cost of inaction) and an under-prioritization of positive risk. Correspondingly for wildfires as an example, there is an under-recognition of the potential shared value upside of preventative action through social innovation and social interventions (such as goats & sheep that prevent wildfires). CrowdDoing.world's aim is to guarantee positive risk through leveraging existing liabilities to allow for the implications of prescriptive analytics to be financed. The under-pricing of passive risk means that liabilities are treated as either costs of doing business or un-predictable risks even for entirely preventable risks. Risk management offices have been too biased towards avoiding taking the wrong risks rather than ensuring that institutions make their own luck by seizing the abundant positive risk opportunities in social innovation. Meanwhile, the bias against positive risk leaves social innovations not to get adopted even if there would be remarkable benefits to all stakeholders if they were adopted
Data science will be utilized in the following ways:
Explore/Visualize data currently available on Wildfires
Identify trends and patterns in Historical data
Quantify historical losses in dollars based on property destruction, casualties, acres burnt, etc.
Build predictive models to identify areas of high wildfire risk based on factors such as weather, vegetation, topography, etc.
Visualization of Model outcomes
Scenario building (changing input variables and observing impact on outcome)
Tools - R, Python, MATLAB, SQL, PowerPoint
Knowledge or Interest in anyone or more:
Programming for Data Science
Mathematics
Statistics
Predictive Analytics
Prescriptive Analytics
Machine Learning - Supervised/Unsupervised learning
Artificial Intelligence
Data Mining
Computer Science
Monte Carlo Simulations
Expectations:
Identify papers on Simulation of Wildfires, Catastrophe Modeling
Review and present Technical papers in a way that everyone can understand
Assist in Model development and testing by contributing in finding data and programming
Identify/Collect data relevant to wildfire Impact
Work cross-functionally
Traits:
Mathematically inclined, highly analytical, creative problem solver, can conduct analyses independently or with minimal supervision

If you have any questions about processes for joining CrowdDoing.world as a volunteer to support our efforts in systemic change please write to volunteerorientation@crowddoing.world

Opportunity Details

Fortune 500 Risk Simulation based on PGE Bankruptcy Data for Wildfire Risk
Prevention Derivatives draws upon the annual recurring expected losses of Fortune 1000 companies. It would be helpful to do more with the data on the PGE bankrupsy to fully simulate the 75 Fortune 500 companies that expect that loss to recur at 2.5% to 10%.
-Prevention derivatives is driven by the thesis that there is an under-valuation of passive risk (or the cost of inaction) and an under-prioritization of positive risk. Correspondingly for wildfires as an example, there is an under-recognition of the potential shared value upside of preventative action through social innovation and social interventions (such as goats & sheep that prevent wildfires). CrowdDoing.world's aim is to guarantee positive risk through leveraging existing liabilities to allow for the implications of prescriptive analytics to be financed. The under-pricing of passive risk means that liabilities are treated as either costs of doing business or un-predictable risks even for entirely preventable risks. Risk management offices have been too biased towards avoiding taking the wrong risks rather than ensuring that institutions make their own luck by seizing the abundant positive risk opportunities in social innovation. Meanwhile, the bias against positive risk leaves social innovations not to get adopted even if there would be remarkable benefits to all stakeholders if they were adopted

In the framework of Prevention Derivatives, we want to create a predictive machine learning (ML) model that for a given geographical region will estimate likely savings (losses) due-to protection (damages) of stakeholders’ properties, business profits, common health, and regional ecology resulting in applying risk prevention solutions (or doing nothing instead). Goal of these notes is to analyze ML model’s design, offer a potential improvement and to discuss existing approaches for data collection, and training and testing the model. It is important to notice that the model is applied to the entire selected or target region. Therefore, a geographical region R is the smallest unit we apply modeling to.
Data science will be utilized in the following ways:
Explore/Visualize data currently available on Wildfires
Identify trends and patterns in Historical data
Quantify historical losses in dollars based on property destruction, casualties, acres burnt, etc.
Build predictive models to identify areas of high wildfire risk based on factors such as weather, vegetation, topography, etc.
Visualization of Model outcomes
Scenario building (changing input variables and observing impact on outcome)
Tools - R, Python, MATLAB, SQL, PowerPoint
Knowledge or Interest in anyone or more:
Identify papers on Simulation of Wildfires, Catastrophe Modeling
Review and present Technical papers in a way that everyone can understand
Assist in Model development and testing by contributing in finding data and programming
Identify/Collect data relevant to wildfire Impact
Work cross-functionally
Traits:
Mathematically inclined, highly analytical, creative problem solver, can conduct analyses independently or with minimal supervision
Programming for Data Science
Mathematics
Statistics
Predictive Analytics
Prescriptive Analytics
Machine Learning - Supervised/Unsupervised learning
Artificial Intelligence
Data Mining
Computer Science
Monte Carlo Simulations
Expectations:

If you have any questions about processes for joining CrowdDoing.world as a volunteer to support our efforts in systemic change please write to volunteerorientation@crowddoing.world

Opportunity Details

Positive Risk Management/Opportunity Management Literature Reviewer, Wildfire Prevention CrowdDoing
Prevention Derivatives draws upon "positive risk" and "opportunity management". We are scaling this sector up. Reviewing the literature here could be helpful.
-Prevention derivatives is driven by the thesis that there is an under-valuation of passive risk (or the cost of inaction) and an under-prioritization of positive risk. Correspondingly for wildfires as an example, there is an under-recognition of the potential shared value upside of preventative action through social innovation and social interventions (such as goats & sheep that prevent wildfires). CrowdDoing.world's aim is to guarantee positive risk through leveraging existing liabilities to allow for the implications of prescriptive analytics to be financed. The under-pricing of passive risk means that liabilities are treated as either costs of doing business or un-predictable risks even for entirely preventable risks. Risk management offices have been too biased towards avoiding taking the wrong risks rather than ensuring that institutions make their own luck by seizing the abundant positive risk opportunities in social innovation. Meanwhile, the bias against positive risk leaves social innovations not to get adopted even if there would be remarkable benefits to all stakeholders if they were adopted

In the framework of Prevention Derivatives, we want to create a predictive machine learning (ML) model that for a given geographical region will estimate likely savings (losses) due-to protection (damages) of stakeholders’ properties, business profits, common health, and regional ecology resulting in applying risk prevention solutions (or doing nothing instead). Goal of these notes is to analyze ML model’s design, offer a potential improvement and to discuss existing approaches for data collection, and training and testing the model. It is important to notice that the model is applied to the entire selected or target region. Therefore, a geographical region R is the smallest unit we apply modeling to.
Data science will be utilized in the following ways:
Explore/Visualize data currently available on Wildfires
Identify trends and patterns in Historical data
Quantify historical losses in dollars based on property destruction, casualties, acres burnt, etc.
Build predictive models to identify areas of high wildfire risk based on factors such as weather, vegetation, topography, etc.
Visualization of Model outcomes
Scenario building (changing input variables and observing impact on outcome)
Tools - R, Python, MATLAB, SQL, PowerPoint
Knowledge or Interest in anyone or more:
Identify papers on Simulation of Wildfires, Catastrophe Modeling
Review and present Technical papers in a way that everyone can understand
Assist in Model development and testing by contributing in finding data and programming
Identify/Collect data relevant to wildfire Impact
Work cross-functionally
Traits:
Mathematically inclined, highly analytical, creative problem solver, can conduct analyses independently or with minimal supervision
Programming for Data Science
Mathematics
Statistics
Predictive Analytics
Prescriptive Analytics
Machine Learning - Supervised/Unsupervised learning
Artificial Intelligence
Data Mining
Computer Science
Monte Carlo Simulations
Expectations:

If you have any questions about processes for joining CrowdDoing.world as a volunteer to support our efforts in systemic change please write to volunteerorientation@crowddoing.world

Opportunity Details

Exploring New Horizons (ENH) seeks board members to help support our San Francisco Bay Area outdoor education non profit. Board members serve as advocates of ENH, meet 4 times a year, serve on a committee, and support the organization with time and or financial donations.

Currently, ENH is specifically seeking board members with a background in fundraising, financial management, and with a legal background.

Please contact ENH Executive Director, Jacob Sackin, if interested. jacob@exploringnewhorizons.org

Available Shifts

Shift Name	Signup Max	Start	End
General	no limit	n/a	n/a

Opportunity Details

Friends of Charlotte-Mecklenburg Animal Care & Control (Animal Services) is looking for new members and volunteers to help raise awareness of CMPD Animal Care & Control programs and services and develop fundraising activities to fund the programs.

Opportunity Details

Foundations In Education recruits qualified volunteers to serve on Board committees that guide our programs and operatoins. Committee members are vetted for skill set match and ultimately appointed by the Board Chair. Committees include Scholarship Distribution, Marketing, Innovation and Leadership, etc.

Available Shifts

Shift Name	Signup Max	Start	End
Meetings are scheduled as needed, according to the program calendar.	5	n/a	n/a

Opportunity Details

Refugee Camp in My Neighbourhood provides a powerful immersive learning experience for participants to experience the journey of a refugee, led by guides with ‘lived experience’ from a range of refugee and asylum seeker backgrounds. The project also provides training and employment opportunities, building confidence and providing pathways for longer term employment for people from refugee backgrounds. The tours are confronting, powerful and life-changing - watch this video to find out more.
Our current website (www.refugeecampauburn.com.au), however, doesn't have the same impact as our tours and needs an urgent refresh/revamp (just take a look)!
Do you have ideas to improve the site? It could be as simple as a new WordPress template that we can manage ourselves … it just needs to look better!
Other improvements could include incorporating our online EOI process for schools or managing bookings for tours and booking confirmation information etc, but these are longer terms goals. For now we need an urgent and quick refresh (our promo has already started!).
The kind person will be very competent at designing a web page. They will be able to be creative in the design probably using a simple CMS such as wordpress or something easy for us to use when making changes in the future.
If you have ideas and skills in this area, we would love to discuss further.

Available Shifts

Shift Name	Signup Max	Start	End
Website resdesign	no limit	n/a	n/a

Opportunity Details

At the Chike Springer Foundation, our mission is to improve Lymphoma treatment outcomes and increase diversity in cancer research. We are hosting our first fundraising event, called the Overcome Fitness Fundraising Challenge! This fun, month-long challenge will help raise much-needed funds for innovative cancer research and support our mentorship program.
 
We’d like you to spread the word to your community, as well as promote on social media. We’re inviting groups from around the country to overcome any obstacles that stand in their way, and any activity counts! - Any workout, run, swim, or yoga counts!
 
For more information on us, you can visit our website. To get registered and join the challenge, you can visit our event website here or reach out to me directly at lspringer@chikespringerfoundation.org.
 
Thank you for helping to find a cure for Lymphoma and promoting diversity in cancer research!

Available Shifts

Shift Name	Signup Max	Start	End
General	200	n/a	n/a