Replacement of the Legacy High-Cost Universal Support Fund with a Connect America Fund. Key Economic and Legal Considerations

On April 21, 2010, the Federal Communications Commission (FCC) released a Notice of Inquiry (NOI) and a Notice of Proposed Rulemaking (NPRM) that seek the public’s input on the FCC’s effort to replace the legacy high-cost universal service fund (USF) with a broadband “Connect America” fund (CAF). In effect, the FCC seeks to implement cost-cutting measures for existing voice support (USF) and create a new fund (CAF) to support the provision of broadband communications in areas that would be unserved without such support or that depend on USF support for the maintenance of existing broadband service. An initial review of the NOI/NPRM raises a number of key economic and legal considerations. In the following, we identify some of the considerations, questions, and challenges raised by the FCC’s USF reform attempt, which is likely to have far-reaching consequences not only for operators that currently rely on USF subsidies or broadband providers in high-cost regions but for the entire communications industry.The purpose of this note is not to provide an all-inclusive list of, or responses to, the critical questions raised by the NOI/NPRM, but rather to illustrate the complexities of this proceeding and the impact the proposed reforms may have on industry performance. As the CAF is necessary for the success of the FCC’s National Broadband Plan (NBP), the policy directions taken by the FCC in establishing it are critically important. USF reform is also essential to the performance and competitiveness of the U.S. communications industry and policy missteps could have serious economic and legal consequences.Federal Communications Commission, America Fund

A Cognitive Modeling Approach for Predicting Behavioral and PhysiologicalWorkload Indicators

Measuring cognitive workload is a persistent challenge in cog-nitive science. Cognitive architectures may offer a prin-cipledway to measure, define, and understand workload and its be-havioral and physiological consequences in terms ofunder-lying cognitive dynamics. Previous research has shown thatmodel-based workload relates to subjective workloadjudg-ments in simple tasks. Our goal was to further validate model-based workload measurement with known physiolog-ical work-load indicators in a complex task characterized by varying de-grees of workload levels. Participants completedan unmannedvehicle management task while their physiology was recorded.Correlations between model-based workloadand physiologi-cal metrics generally trended in the predicted direction, andthe engagement index showed the strongest andmost consis-tent relationship to model workload. The results provide pre-liminary validation for model-based workloadmeasurement

Marinello One Acts: Calm Down Mother, and The Actor\u27s Nightmare

Calm Down Mother is a collection of unrelated scenes, while The Actor\u27s Nightmare employs a play within a play to present a parody of life and its institutions. These were performed at John Carroll University in February of 1998.https://collected.jcu.edu/plays/1108/thumbnail.jp

The mass-L_x relation for moderate luminosity X-ray clusters

We present measurements of the masses of a sample of 25 moderate X-ray luminosity clusters of galaxies from the 160 square degree ROSAT survey. The masses were obtained from a weak lensing analysis of deep F814W images obtained using the Advanced Camera for Surveys (ACS). We present an accurate empirical correction for the effect of charge transfer (in)efficiency on the shapes of faint galaxies. A significant lensing signal is detected around most of the clusters. The lensing mass correlates tightly with the cluster richness. We measured the intrinsic scatter in the scaling relation between M_2500 and L_X and find the best fit power law slope and normalisation to be alpha=0.68+-0.07 and M_X=(1.2+-0.12)10^14M_sun (for L_X=2x10^44 erg/s). These results agree well with a number of recent studies, but the normalisation is lower compared to the study of Rykoff et al. (2008b). One explanation for this difference may be the fact that (sub)structures projected along the line-of-sight boost both the galaxy counts and the lensing mass. Such superpositions lead to an increased mass at a given L_X when clusters are binned by richness.Comment: accepted for publication in the Astrophysical Journal; 15 pages, 11 figure

Algorithmic Risk Assessments and the Double-Edged Sword of Youth

Risk assessment algorithms—statistical formulas that predict the likelihood a person will commit crime in the future—are used across the country to help make life-altering decisions in the criminal process, including setting bail, determining sentences, selecting probation conditions, and deciding parole. Yet many of these instruments are “black-box” tools. The algorithms they use are secret, both to the sentencing authorities who rely on them and to the offender whose life is affected. The opaque nature of these tools raises numerous legal and ethical concerns. In this paper we argue that risk assessment algorithms obfuscate how certain factors, usually considered mitigating by sentencing authorities, can lead to higher risk scores and thus inappropriately inflate sentences. We illustrate this phenomenon through one of its most dramatic manifestations: The role of age in risk assessment algorithms. When considered as a factor at sentencing, youthfulness can be a double-edged sword—it can both enhance risk and diminish blameworthiness. If either risk or culpability is the sole issue at sentencing, this potential conflict is avoided. But when, as is often the case, both risk and culpability are considered relevant to the sentence, the aggravating effect of youth should presumably be offset or perhaps eliminated entirely by its mitigating impact. If judges and parole authorities are fully informed of the conflicting roles youth plays in a particular case, they can engage in this balancing act as appropriate. However, when information about risk comes from a black-box algorithm, they are unlikely to know the extent to which the risk evaluation is influenced by the defendant’s youthfulness. In such cases, their decisions about pretrial detention, sentence, or release may unknowingly give youth too much weight as an aggravator. Further, even if the black box is opened and the risk assessment algorithm is made publicly available, the risk score may not be conveyed in a fully transparent manner. For instance, while judges may be told that an offender’s youth is a risk factor, the relative weight of age in the overall score may not be fully explained or understood at the time of decision-making. Unless the judge makes specific inquiries, she will not be informed of the variables that contributed most heavily to a particular defendant’s risk score. This decisional blindness is especially pernicious in light of the impression created by the labels associated with these instruments—“high risk” or “high risk of violence.” Such labels not only convey information about the potential for recidivism. They are also suggestive of bad character, or at least a history of bad decision-making. In other words, these labels convey condemnation. Such condemnation might be appropriate for an individual who has earned the “high-risk” classification by committing multiple violent or ruthless acts. But it is not warranted for an individual who has earned that label largely because of his or her youth. To ensure sentencers take this double-edged sword problem into account, risk assessment algorithms should be transparent about the factors that most heavily influence the score. Only in that way can courts and legislators engage in an explicit discussion about whether, and to what extent, young age should be considered a mitigator or an aggravator in fashioning criminal punishment. In Part I, we discuss the tensions youthfulness generates in the post-conviction setting by introducing the double-edge sword phenomenon and the jurisprudence that has developed around it. In Part II, we present empirical evidence that shows how influential age is in the widely-used COMPAS Violent Recidivism Risk Score (VRRS) and in other common risk assessment tools. Specifically, we conduct a partial decomposition of the VRRS to show that age alone can explain almost 60% of its variation, substantially more than the contributions of criminal history, gender or race. Similar patterns are documented in other common risk scores. In Part III, we discuss how obfuscation of age’s impact on the risk score improperly undermines consideration of youthfulness as a mitigating factor. We also discuss how the points we make about the role of youth might apply to a number of other factors that are often used in structured risk assessments, including mental illness, substance abuse, and socio-economic factors. While our discussion centers on sentencing, the main argument is generally relevant to a broad range of settings in which risk assessments influence criminal justice outcomes

CHA Residents and the Plan for Transformation

This series of policy briefs presents findings from more than a decade of research on the people who lived in Chicago Housing Authority properties when the agencylaunched its Plan for Transformation in October 1999. The ongoing, multiyear effort sought to improve resident well-being by renovating or demolishing decaying public housing properties and replacing them with new, mixed-income development

Toward Modeling Pilot Workload in a Cognitive Architecture

Characterizing and predicting pilot cognitive workload remains a formidable challenge, especially in tasks with a high perceptual/motor demand like aerial refueling. Cognitive models are useful tools for this, as they offer the potential to derive both performance and workload simulations before a test is conducted. We conducted a task analysis of a C-17 aerial refueling mission and developed a low-fidelity Atomic Components of Thought – Rational (ACT-R) model and environment to simulate the task. ACT-R models have been successful in predicting workload in other domains, such as menu navigation and problem solving. Eight aerial maneuvers were examined, including takeoff, climb, cruise, descent, refueling, contact station keeping, and landing. The exercise revealed two subtasks not currently described in great detail by workload modeling methods: trajectory estimation and collision avoidance. We identify gaps in research on workload modeling approaches and explore preliminary predictions made by the model using default ACT-R parameters