Penn Law Journal: An Rx to Heal Criminal Justice
Bibliographic record
Abstract
rules being added to rule books, enough activities being looked at in new ways In terms of the quality of regulation, I am less sure.I think fundamentally the prevention of financial crisis depends upon institutions having adequate amounts of capital and liquidity Whether we will or will not succeed in achieving those levels remains to be seen.Because everybody is still very nervous and gun shy after the crisis I would be quite surprised if the economy went back into crisis in the near term.But do we have sufficient antidotes in place to make complacency impossible in the future?I'm not sure that we do and I'm not sure that we ever could.But I would hope for approaches that focus on the assumption that there is going to be ignorance and greed, and working to make the system safe under those circumstances, rather than trying to combat those forces.wHat do you consider tHe biggest current tHreat to global economic growtH, and How does tHat track witH wHat is occurring in america?One obvious threat is geopolitical uncertainty, whether it's in Russia and Ukraine, whether it's chaos in the Middle East, whether it's the strains associated with the rise of China.A second uncertainty surrounds the very serious challenges facing other parts of the industrialized world besides the United States.Abenomics (the name of the economic recovery program proposed by Japanese Prime Minister Shinzo Abe) has not yet proven successful.Japan in the second quarter saw 'growth' at almost negative 7 percent.And Europe is on the brink of deflation.In an increasingly integrated world that has to have consequences for us as well."Litigators and trial attorneys who understand the digital footprint and digital data are in a much better position not only to advocate for their clients, but to do so cost-effectively," Kessler said."If you don't know the facts, you can't advocate," added Kessler, who is co-head of E-Discovery and the Information Governance Practice in the New York office of Fulbright & Jaworski LLP."In the digital world, facts are buried under a mountain of data."Kessler offered statistics delineating the galloping growth of data.Between 2003 and 2010, the world generated as much data every two months as it had from the dawn of civilization to that point.Last year, we created the same amount of data every two days.In his seminar, he teaches students how to deal with that deluge.Specifically, Kessler teaches students how to conduct preservation, develop search terms, negotiate with opponents, and how to forensically examine a disc or hard drive."In this economy and in a very competitive legal world, that kind of advantage is a really important thing both for junior and senior lawyers," Kessler said.He conceded, however, that there are obstacles to E-Discovery in an integrated world.Some countries, like members of the European Union, he said, often have more stringent and holistic privacy laws than the United States, which can make it more difficult for American lawyers to conduct U.S. style discovery that crosses borders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".