Wikipedia – en.wikipedia.org/wiki/ Community policing, or community-oriented policing (COP), is a strategy of policing that focuses on building ties and working closely with members of the community. It is a philosophy of full-service policing that is highly personal, where an officer patrols the same area for a period of time and develops a partnership with citizens to identify and solve problems.
The central goal of community policing is for the police to build relationships with the community,
including through local agencies to reduce social disorder. Although community policing mostly targets low-level crime, the broken windows theory proposes that this can reduce more serious crime as well.
Community policing is related to problem-oriented policing and intelligence-led policing, and contrasts with reactive policing strategies which were predominant in the late 20th century.[10] Many police forces have teams that focus specifically on community policing, such as Neighbourhood Policing Teams in the United Kingdom, which are separate from the more centralized units that respond to emergencies.
What are the strategies of community policing?
The three key components of community policing strategies are organizational transformation, community partnerships, and shared problem solving.
Common methods of community-policing include:
Encouraging the community to help prevent crime by providing advice, talking to students and encouraging neighborhood watch groups Increased use of foot or bicycle patrols. Increased officer accountability to the communities they serve Creating teams of officers to carry out community policing in designated neighborhoods. Clear communication between the police and the communities about their objectives and strategies. Partnerships with other organizations such as government agencies, community members, nonprofit service providers, private businesses and the media. Moving towards some decentralizing of the police authority, allowing more discretion among lower-ranking officers, and more initiative expected from them.
What is an example of community policing?
Neighborhood watches are an example of community policing in action, and these are when residents set up teams to routinely keep an eye out for potential criminal activity. Along these lines are “walk throughs”, which also involve citizens on the alert for crime, and ready to report it.
What to know about community policing?
Community policing stresses prevention, early identification, and timely intervention to deal with issues before they become unwieldy problems. Individual officers tend to function as general-purpose practitioners who bring together both government and private resources to achieve results.
New tool can diagnose strokes with a smartphone
Date : October 22, 2020
Source:
Penn State
Summary:
A new tool could diagnose a stroke based on abnormalities in a patient’s speech ability and facial muscular movements, and with the accuracy of an emergency room physician — all within minutes from an interaction with a smartphone.
FULL STORY
A new tool created by researchers at Penn State and Houston Methodist Hospital could diagnose a stroke based on abnormalities in a patient’s speech ability and facial muscular movements, and with the accuracy of an emergency room physician — all within minutes from an interaction with a smartphone.
“When a patient experiences symptoms of a stroke, every minute counts,” said James Wang, professor of information sciences and technology at Penn State. “But when it comes to diagnosing a stroke, emergency room physicians have limited options: send the patient for often expensive and time-consuming radioactivity-based scans or call a neurologist — a specialist who may not be immediately available — to perform clinical diagnostic tests.”
Wang and his colleagues have developed a machine learning model to aid in, and potentially speed up, the diagnostic process by physicians in a clinical setting.
“Currently, physicians have to use their past training and experience to determine at what stage a patient should be sent for a CT scan,” said Wang. “We are trying to simulate or emulate this process by using our machine learning approach.”
The team’s novel approach is the first to analyze the presence of stroke among actual emergency room patients with suspicion of stroke by using computational facial motion analysis and natural language processing to identify abnormalities in a patient’s face or voice, such as a drooping cheek or slurred speech.
The results could help emergency room physicians to more quickly determine critical next steps for the patient. Ultimately, the application could be utilized by caregivers or patients to make self-assessments before reaching the hospital.
“This is one of the first works that is enabling AI to help with stroke diagnosis in emergency settings,” added Sharon Huang, associate professor of information sciences and technology at Penn State.
To train the computer model, the researchers built a dataset from more than 80 patients experiencing stroke symptoms at Houston Methodist Hospital in Texas. Each patient was asked to perform a speech test to analyze their speech and cognitive communication while being recorded on an Apple iPhone.
“The acquisition of facial data in natural settings makes our work robust and useful for real-world clinical use, and ultimately empowers our method for remote diagnosis of stroke and self-assessment,” said Huang.
Testing the model on the Houston Methodist dataset, the researchers found that its performance achieved 79% accuracy — comparable to clinical diagnostics by emergency room doctors, who use additional tests such as CT scans. However, the model could help save valuable time in diagnosing a stroke, with the ability to assess a patient in as little as four minutes.
“There are millions of neurons dying every minute during a stroke,” said John Volpi, a vascular neurologist and co-director of the Eddy Scurlock Stroke Center at Houston Methodist Hospital. “In severe strokes it is obvious to our providers from the moment the patient enters the emergency department, but studies suggest that in the majority of strokes, which have mild to moderate symptoms, that a diagnosis can be delayed by hours and by then a patient may not be eligible for the best possible treatments.”
“The earlier you can identify a stroke, the better options (we have) for the patients,” added Stephen T.C. Wong, John S. Dunn, Sr. Presidential Distinguished Chair in Biomedical Engineering at the Ting Tsung and Wei Fong Chao Center for BRAIN and Houston Methodist Cancer Center. “That’s what makes an early diagnosis essential.”
Volpi said that physicians currently use a binary approach toward diagnosing strokes: They either suspect a stroke, sending the patient for a series of scans that could involve radiation; or they do not suspect a stroke, potentially overlooking patients who may need further assessment.
“What we think in that triage moment is being either biased toward overutilization (of scans, which have risks and benefits) or underdiagnosis,” said Volpi, a co-author on the paper. “If we can improve diagnostics at the front end, then we can better expose the right patients to the right risks and not miss patients who would potentially benefit.”
He added, “We have great therapeutics, medicines and procedures for strokes, but we have very primitive and, frankly, inaccurate diagnostics.”
Other collaborators on the project include Tongan Cai and Mingli Yu, graduate students working with Wang and Huang at Penn State; and Kelvin Wong, associate research professor of electronic engineering in oncology at Houston Methodist Hospital.
Business Insider
Tyler Sonnemaker October 13, 2020
A California appeals court heard arguments on Tuesday from Uber and Lyft as they appeal a recent ruling that would force the companies to reclassify drivers as employees.
A lower court determined in August that Uber and Lyft drivers are employees, not contractors, under the state’s gig work law, AB-5, but delayed enforcing the ruling while the companies appeal it.
Uber, Lyft, and other gig companies have fought AB-5 aggressively, pouring more than $180 million into a ballot measure aimed at California voters that would permanently exempt them from the law.
Uber CEO Dara Khosrowshahi and Lyft CEO Logan Green Laura Buckman/Reuters; Carlo Allegri/Reuters
The companies argue reclassifying drivers as employees will reduce their flexibility, while proponents of AB-5 say Uber and Lyft’s business models rely on underpaying drivers and skirting labor laws.
A California appeals court heard oral arguments Tuesday from Uber, Lyft, and the state over whether a lower court reached the right conclusion in August when it ruled that the companies’ drivers are employees under the state’s gig work law, AB-5.
Judges from California’s first district Court of Appeal pressed lawyers for Uber and Lyft over drivers’ wages and autonomy, and questioned the companies’ arguments that AB-5 would require them to reduce drivers’ flexibility, according to The Washington Post and The New York Times reporter Kate Conger.
The judges also asked a lawyer for the state about potential harms to Uber and Lyft and drivers’ preferences around their employment status, according to reports.
The landmark case could fundamentally alter the contractor-based business model that Uber and Lyft have relied on, and the companies are aggressively fighting the law in court and via a ballot measure that California voters will decide on in November.
AB-5, which went into effect at the beginning of this year, allows companies to treat workers as independent contractors instead of employees only if workers meet three criteria: they’re “free from the control and direction” of the company; they perform work “outside the usual course” of the company’s business; and they’re “customarily engaged” in their own independent business.
California state and city attorneys general sued Uber and Lyft in May over their refusal to comply with the law, arguing that ride-hailing drivers don’t pass that test. San Francisco Superior Court Judge Ethan Schulman sided with the state in August, ruling that Uber and Lyft must reclassify drivers as employees, but the ruling was stayed by Schulman and again by the appellate court while the companies appeal.
In Tuesday’s oral arguments, Uber lawyer Theodore Boutrous Jr. argued the ruling would cause “irreparable harm” and that “Uber would have to turn into a different company” and cut jobs if the ruling is upheld, The Washington Post reported.
But according to Conger, Judge Brown questioned Uber on that claim, asking what part of AB-5 would require the company to reduce drivers’ flexibility.
Uber and Lyft have focused heavily on flexibility in their opposition to the law, citing drivers’ alleged preference to work as contractors, but critics of the business model say it allows the companies to cut costs by depriving drivers of protections like minimum wage, health insurance, and unemployment insurance that other California workers are entitled to.
Matthew Goldberg, a lawyer from the San Francisco city attorney’s office, responded to a question about drivers’ preferences by saying “employees should not have the right to work without those underlying benefits. … You are not permitted to work for less than the minimum wage, even if you want to.”
When pressed by the judges on potential harms to Uber and Lyft, Goldberg responded that every other company follows the law and so Uber and Lyft should have to as well, The New York Times’ Kate Conger tweeted. He also said Uber and Lyft were causing harm to drivers: “This is dollars and wages and money that is being stolen from drivers by virtue of the misclassification.”
Uber and Lyft have repeatedly claimed that the law doesn’t apply to them in the first place — an argument Lyft lawyer Rohit Singla brought up again Tuesday, while Boutrous cited changes Uber has made to its app that should exempt its drivers, according to The Washington Post.
But the judges appeared skeptical, Conger reported, pointing out that Uber still sets the base fare for drivers.
They also cast doubt on Lyft’s claim that underpayment of drivers’ wages isn’t irreparable harm, according to The Washington Post, with one asking: “Are you suggesting that the specter of thousands of individual claims for back wages is something that is insignificant and something that need not be considered in balancing the appropriateness of an injunction at this point?”
California’s Labor Commission brought a separate lawsuit against Uber and Lyft over the same issue in August, alleging they’ve been committing wage theft by classifying drivers as contractors.
Uber and Lyft have sought to head off a potential loss in court by pouring more than $180 million into a ballot measure, Proposition 22, that would exempt ride-hail and food delivery workers from AB-5. That’s the most money ever used to back a ballot measure in the state, according to Ballotpedia.
Uber and Lyft also came under fire earlier this week after SF Gate reported that the companies indirectly funded ballot guides sent to California voters urging them to vote for Proposition 22 by falsely claiming to be affiliated with Sen. Bernie Sanders and other “progressive” groups.
The central goal of community policing is for the police to build relationships with the community, 
