If we can harness "big data" to elect a president, we can shift the trajectory of too many of our city's young men from future incarceration. Using the same techniques, we can identify and create conditions through small changes that enable a trajectory more conducive to success in the legal economy for men.

Demographic and historical data analysis can predict which facts/factors in a very large data sample of boys potentially influence their candidacy for a future in prison. More importantly, it can also enable near real-time evaluation of circumstances, events, and actions that potentially influence their path. Through small changes, we might favorably impact that future for our local, hometown boys.

The goal is not to find the answer to what makes children grow up to be criminals, because that changes over time and based on current events, opportunities, obstacles, situations, economics, and many other conditions. The factor in the Obama campaign's success was the ability to quickly discover and respond to changes in opinion, perceptions, and behavior of the targeted populations.

In the case of the election, the focus was on voters in the swing states. The focus for this proposal is populations of boys and young men who are, statistically, demographically, and characteristically speaking, a good match for the current population of Oakland boys and young men. The goal is to analyze large quantities of small, but relevant, facts and indicators about this population to discern what might be happening right now to affect their perceptions, decisions and actions. We can quickly evaluate which influencers and responses are more or less effective, favorably or unfavorably.

In addition, these techniques can be used to identify shifts in Oakland community perception, culture and behavior, e.g. among prospective employers, to identify strategies and tactics to favorably influence them on behalf of the target population.