MétaCan
Menu
Back to cohort
Record W7025104901

UND Police’s first K-9 officer sworn in; ready to take a bite out of area crime

2014· article· en· W7025104901 on OpenAlexaboutno aff

Bibliographic record

VenueUND Scholarly Commons (University of North Dakota) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerParaphernaliaCeremonySubject (documents)Law enforcement
DOInot available

Abstract

fetched live from OpenAlex

UND Police’s first K-9 officer sworn in; ready to take a bite out of area crime University of North Dakota K-9 Police Officer "Ben," a two-year-old yellow Labrador retriever, raised his right paw and wondered what all the hub-bub was about. Cloaked in a specially modified bullet-proof vest, the dog, flanked by about a dozen of his fellow University Police Department officers, took an oath of service to upload the policies and laws of the University, the University System and the State of North Dakota at a special swearing-in ceremony held Monday, Aug. 11, at the Chester Fritz Auditorium. UND Police Chief Eric Plummer held Ben's paw and administered the oath, while Ben's handler, human Officer Jose Solis, recited the words for his four-legged partner in crime fighting. The duo promised to do all it could to take a bite out of crime on campus and in the community. Solis' wife, Ashley, and his 16-month-old daughter, Abigail, took part in the ceremony by pinning Ben's police badge to his vest. Just last week, after only a few days on the job, Ben assisted in his first arrest, when he was called to the scene of a routine traffic stop. The dog "alerted" to the presence of a substance inside the vehicle. During the search of the vehicle, officers discovered components commonly used in the manufacturing of methamphetamine. Two suspects were arrested and charged in that incident. Humans, too Ben wasn't the only new UPD officer to be sworn in Monday. Frank LaNasa Jr., 25, a native of St. Paul and Isanti, Minn., took the oath of service as well. LaNasa was joined at the ceremony by his father, Frank Sr., who pinned the badge on his son, and mother, Jean, his girlfriend, Urelle Stangler, and Mack Johnson, Frank Jr.'s longtime friend from Grand Forks. A visibly proud Jean LaNasa embraced her son and showed tears of joy following the ceremony. "I'm just bursting, right now," she said. As a boy, Officer Frank LaNasa remembers going on multiple ride-alongs with his uncle, a member of the Minneapolis Police Force. That was enough to interest him following his uncles footsteps. LaNasa graduated from the Minnesota State University Mankato with a bachelor's degree in law enforcement studies. In 2012, he completed his Minnesota police certification course in Hibbing, Minn. LaNasa formerly worked as a security officer in St. Paul. Ben, the dog, was born on Feb. 21, 2012 outside West Fargo. He was bred to be a hunting dog, but his career took a sharp turn toward law enforcement in 2013 when he was purchased by the operator of Northwest Iowa K-9. Ben is a certified narcotics detection K-9 and is able to detect the odors of marijuana, cocaine, meth, heroin and their sister narcotics. The dog's other skill is in finding missing people and items. Ben was purchased for UPD in July with the help of the UND Association of Residence Halls. The dog works and lives with Officer Solis. About 40 members of the public, including UND administrators Provost Thomas DiLorenzo, Vice President for Finance & Operations Alice Brekke and Vice President for University & Public Affairs Susan Walton, were on hand for the ceremony. Plummer said, like all his officers, both Officer LaNasa and Ben embody the values of UPD: integrity, courtesy, service and professionalism. "They will make a big difference not only on our campus but also in our community," Plummer said. Check out the UPD Twitter account for news and updates. David Dodds University & Public Affairs writer

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.070
GPT teacher head0.317
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueUND Scholarly Commons (University of North Dakota)Same topicPolicing Practices and PerceptionsFrench-language works237,207