Posts tagged New Mexico
Buffs Hold Off No. 8 Cardinals At The Wire
Dec 15th
BOULDER – The buildup was big, but Colorado’s effort was bigger. The CU women’s basketball team took on – and took down – No. 8 Louisville 70-66 on Friday night at the Coors Events Center.
But it wasn’t easy for the Buffaloes to remain unbeaten (9-0).
CU led by as many as 13 (64-51) in the final 3 minutes before Louisville’s full-court pressure sparked a 10-0 run and allowed the Cardinals to close to 68-66 in the final half-minute.
But Jen Reese scored on a critical put-back after two missed free throws by Brittany Wilson with 11.1 seconds remaining to give the Buffs their first win against a Top Ten opponent since the 2002 CU team defeated No. 5 Stanford in the NCAA’s Sweet 16. Buffs coach Linda Lappe was a junior on that squad.
The Buffs had four players in double figures, topped by Chucky Jeffery’s 22. Arielle Roberson added 13 and Reese and Wilson had 11 each. CU center Rachel Hargis contributed seven points and a career-high seven blocks.
Louisville (9-2) was led by Antonita Slaughter’s 19. Cardinals’ leading scorer Shoni Schimmel was held to four.
The Buffs are off until Saturday, Dec. 22 when they host Utah Valley (1:30 p.m.). They close non-conference play a week later against New Mexico (2:30 p.m., Coors Events Center).
Jeffery scored the game’s first basket to give CU a 2-0 lead, but the Buffs trailed for almost the next 10 minutes. The good news: They never let the Cardinals get more than a five-point lead before they made their move to go ahead on a 11-0 run that put them up 23-16.
Roberson scored five points during that spurt, with Jeffery and Lexy Kresl each adding a three-pointer.
Louisville closed the gap to three (23-20) before CU surged again, this time riding Jeffery’s five points and an inside basket by Rachel Hargis on the way to a 7-2 run that gave the Buffs their biggest early lead – 30-22.
Lappe liberally subbed her posts and it paid off. Hargis contributed her best half of the season, hitting three of four field goals, blocking a season-high three shots, collecting two rebounds and getting one steal.
She was on the receiving end of a Jeffery pass in the half’s closing seconds, scoring a layup that put the Buffs up 36-30 at intermission. Jeffery led all first-half scorers with 13 points and was the only player on either team in double figures.
The Buffs held the Cardinals to 39.1 percent from the field (9-for-23) and shut out Schimmel, who entered the game with a team-best 12.1 points a game. Mostly, the job of defending her fell to Brittany Wilson – and “B-Wil” stayed as close as fuzz on a peach.
Louisville entered the game with a plus-9.1 rebounding edge, but was out-boarded 19-12 in the first 20 minutes. CU forced the visitors into 10 first-half turnovers, but matched that total.
The Buffs started the last half in an offensive stupor, not getting their first points until Roberson hit a pair of free throws (38-34) with 15:36 remaining. She followed those with a basket in the lane to push CU ahead again by six (40-34).
But Monique Reid answered with a pair of quick inside buckets to cut the Buffs’ advantage to two (40-38). The Cardinals then pulled to within 41-40 on a bucket by Shawnta Dyer. But the Buffs temporarily held them at bay.
At the 10-minute mark, CU was up 48-43, but a three-pointer by Slaughter trimmed the lead to 48-46. The Buffs held that two-point advantage until Brittany Wilson hit both ends of a one-and-one to up CU’s lead to 50-46 with 7:18 to play.
The Cardinals weren’t done – and the Buffs weren’t even close. A pair of Slaughter free throws pulled them to 50-48 before Jen Reese banked in a short jumper for a 52-48 CU lead with 5:22 showing.
That started a 10-0 Buffs run that produced their biggest lead of the night — 60-49 – with 3:33 remaining.
Here’s how it happened: Jeffery followed with an acrobatic layup to make it 54-48 with just under 5 minutes left, Reese got another basket, and Kresl and Brittany Wilson scored on fast-break lay-ins. The Buffs were up by 11 points, the Cardinals were staggering and the CEC was rocking.
But Louisville’s 10-0 run and a frantic finish were on the way.
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CU Boulder study finds racial ‘hierarchy of bias’ drives decision to shoot armed, unarmed suspects
Oct 24th
Both the police and student subjects were most likely to shoot at blacks, then Hispanics, then whites and finally, in a case of what might be called a positive bias, Asians, researchers found.
In the first study of its kind, Joshua Correll, Bernadette Park and Charles M. Judd of CU-Boulder’s Department of Psychology and Neuroscience and Melody Sadler of San Diego State University examined how police and a group of undergraduate subjects decide whether to shoot or not to shoot “suspects” in a multi-ethnic environment.
“Most studies on the subject of stereotyping and prejudice look at two (ethnic) groups, usually in isolation. It’s always one group against another group,” said Correll, a CU graduate who joined the faculty in August after a stint at the University of Chicago.
“But as the country becomes more ethnically diverse, it’s more and more important to start thinking about how we process racial and ethnic cues in a multicultural environment,” he said.
As with previous studies into the question, data were gathered from subjects playing a “first person shooter” video game, in which figures of varying ethnicity — Caucasian, Asian, Hispanic and African-American — pop up, either “armed” with a weapon or another benign object, such as a cell phone.
Participants — 69 CU-Boulder undergraduates and 254 police officers — had to make quick decisions as to which figures posed a “threat” and shoot them. The police officers were recruited from two-day training seminars in Florida, New Mexico and Washington and represented numerous jurisdictions from 11 states.
The research demonstrates how persistent cultural stereotypes are, Correll said. Even students who displayed little bias when interviewed demonstrated otherwise when faced with a split-second decision.
“I may not believe it personally, but I am exposed to stereotypes constantly through media or social networks … (such as) the idea that young black men are dangerous,” he said. “Those associations can have an influence on my behavior even if I don’t believe them.”
The study found that police were considerably more accurate than students at correctly identifying a genuinely threatening suspect, as opposed to those brandishing a cell phone or wallet, perhaps a reflection of training. But officers were still influenced by the target’s race — an influence that may derive from the officers’ “contacts, attitudes and stereotypes,” Correll said.
For example, police who endorsed more violent stereotypes about Hispanics and those who overestimated the prevalence of violent crime in their districts demonstrated more bias to shoot Hispanic targets. That raises the question of whether police are responding to real-world threats — and whether that means some ethnic groups really are more likely to be armed and dangerous than others.
“That is a very sensitive question, whether or not (police officers’) reactions are based on some kind of truth. Is this police officers responding to reality on the ground? The short answer is, we don’t know,” Correll said. “But this research almost demands that we ask that question.”
The researchers’ recent findings were published in the Journal of Social Issues. The work was funded by a grant from the Russell Sage Foundation.
In 2007, Correll (then at the University of Chicago), Sadler (then at CU-Boulder), Park and Judd collaborated with the Denver Police Department on a widely cited study that found police officers were less influenced than the general public by racial bias and less likely than the general population to make a decision to shoot at African-American suspects wielding a benign object.
-C
CU study says Romney will be Pres
Oct 4th
still points to Romney win,
University of Colorado study says
An update to an election forecasting model announced by two University of Colorado professors in August continues to project that Mitt Romney will win the 2012 presidential election.
According to their updated analysis, Romney is projected to receive 330 of the total 538 Electoral College votes. President Barack Obama is expected to receive 208 votes — down five votes from their initial prediction — and short of the 270 needed to win.
The new forecast by political science professors Kenneth Bickers of CU-Boulder and Michael Berry of CU Denver is based on more recent economic data than their original Aug. 22 prediction. The model itself did not change.
“We continue to show that the economic conditions favor Romney even though many polls show the president in the lead,” Bickers said. “Other published models point to the same result, but they looked at the national popular vote, while we stress state-level economic data.”
While many election forecast models are based on the popular vote, the model developed by Bickers and Berry is based on the Electoral College and is the only one of its type to include more than one state-level measure of economic conditions. They included economic data from all 50 states and the District of Columbia.
Their original prediction model was one of 13 published in August in PS: Political Science & Politics, a peer-reviewed journal of the American Political Science Association. The journal has published collections of presidential election models every four years since 1996, but this year the models showed the widest split in outcomes, Berry said. Five predicted an Obama win, five forecast a Romney win, and three rated the 2012 race as a toss-up.
The Bickers and Berry model includes both state and national unemployment figures as well as changes in real per capita income, among other factors. The new analysis includes unemployment rates from August rather than May, and changes in per capita income from the end of June rather than March. It is the last update they will release before the election.
Of the 13 battleground states identified in the model, the only one to change in the update was New Mexico — now seen as a narrow victory for Romney. The model foresees Romney carrying New Mexico, North Carolina, Virginia, Iowa, New Hampshire, Colorado, Wisconsin, Minnesota, Pennsylvania, Ohio and Florida. Obama is predicted to win Michigan and Nevada.
In Colorado, which Obama won in 2008, the model predicts that Romney will receive 53.3 percent of the vote to Obama’s 46.7 percent, with only the two major parties considered.
While national polls continue to show the president in the lead, “the president seems to be reaching a ceiling at or below 50 percent in many of these states,” Bickers said. “Polls typically tighten up in October as people start paying attention and there are fewer undecided voters.”
The state-by-state economic data used in their model have been available since 1980. When these data were applied retroactively to each election year, the model correctly classifies all presidential election winners, including the two years when independent candidates ran strongly: 1980 and 1992. It also correctly estimates the outcome in 2000, when Al Gore won the popular vote but George W. Bush won the election through the Electoral College.
In addition to state and national unemployment rates, the authors analyzed changes in personal income from the time of the prior presidential election. Research shows that these two factors affect the major parties differently: Voters hold Democrats more responsible for unemployment rates, while Republicans are held more responsible for fluctuations in personal income.
Accordingly — and depending largely on which party is in the White House at the time — each factor can either help or hurt the major parties disproportionately.
In an examination of other factors, the authors found that none of the following had a statistically significant effect on whether a state ultimately went for a particular candidate: The location of a party’s national convention, the home state of the vice president or the partisanship of state governors.
The authors also provided caveats. Their model had an average error rate of five states and 28 Electoral College votes. Factors they said may affect their prediction include the timeframe of the economic data used in the study and that states very close to a 50-50 split may fall in an unexpected direction due to factors not included in the model.
“As scholars and pundits well know, each election has unique elements that could lead one or more states to behave in ways in a particular election that the model is unable to correctly predict,” they wrote.
All 13 election models can be viewed on the PS: Political Science & Politics website at http://journals.cambridge.org/action/displayJournal?jid=PSC.