TREND: Criminal Justice Information Services Division, Federal Bureau of Investigation, Federal Bureau of Investigation. Arrests: Uniform Crime Reporting Population Totals | State: Virginia | County: Amelia, Amherst, Appomattox, Arlington, Augusta, Bath, Bedford, Bedford City, Bland, Botetourt, Bristol, Brunswick, Buchanan, Buckingham, Buena Vista City, Campbell, Caroline, Carroll, Charles City, Charlotte, Charlottesville City, Chesapeake City, Chesterfield, Clarke, Clifton Forge City, Colonial Heights City, Covington City, Craig, Culpeper, Cumberland, Danville City, Dickenson, Dinwiddie, Emporia City, Essex, Fairfax, Fairfax City, Falls Church City, Fauquier, Floyd, Fluvanna, Franklin, Franklin City, Frederick, Fredericksburg City, Galax City, Giles, Gloucester, Goochland, Grayson, Greene, Greensville, Halifax, Hampton City, Hanover, Harrisonburg City, Henrico, Henry, Highland, Hopewell City, Isle Of Wight, James City, King And Queen, King George, King William, Lancaster, Lee, Lexington City, Loudoun, Louisa, Lunenburg, Lynchburg City, Madison, Manassas City, Manassas Park City, Martinsville City, Mathews, Mecklenburg, Middlesex, Montgomery, Nelson, New Kent, Newport News City, Norfolk City, Northampton, Northumberland, Norton City, Nottoway, Orange, Page, Patrick, Petersburg City, Pittsylvania, Poquoson City, Portsmouth City, Powhatan, Prince Edward, Prince George, Prince William, Pulaski, Radford, Rappahannock, Richmond, Richmond City, Roanoke, Roanoke City, Rockbridge, Rockingham, Russell, Salem, Scott, Shenandoah, Smyth, Southampton, Spotsylvania, Stafford, Staunton City, Suffolk City, Surry, Sussex, Tazewell, Virginia Beach City, Warren, Washington, Waynesboro City, Westmoreland, Williamsburg City, Winchester City, Wise, Wythe, York, 2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 010-002-003
Notice bibliographique
Résumé
Criminal Justice Information Services Division, Federal Bureau of Investigation, Federal Bureau of Investigation. Arrests: Uniform Crime Reporting Population Totals | State: Virginia | County: Amelia, Amherst, Appomattox, Arlington, Augusta, Bath, Bedford, Bedford City, Bland, Botetourt, Bristol, Brunswick, Buchanan, Buckingham, Buena Vista City, Campbell, Caroline, Carroll, Charles City, Charlotte, Charlottesville City, Chesapeake City, Chesterfield, Clarke, Clifton Forge City, Colonial Heights City, Covington City, Craig, Culpeper, Cumberland, Danville City, Dickenson, Dinwiddie, Emporia City, Essex, Fairfax, Fairfax City, Falls Church City, Fauquier, Floyd, Fluvanna, Franklin, Franklin City, Frederick, Fredericksburg City, Galax City, Giles, Gloucester, Goochland, Grayson, Greene, Greensville, Halifax, Hampton City, Hanover, Harrisonburg City, Henrico, Henry, Highland, Hopewell City, Isle Of Wight, James City, King And Queen, King George, King William, Lancaster, Lee, Lexington City, Loudoun, Louisa, Lunenburg, Lynchburg City, Madison, Manassas City, Manassas Park City, Martinsville City, Mathews, Mecklenburg, Middlesex, Montgomery, Nelson, New Kent, Newport News City, Norfolk City, Northampton, Northumberland, Norton City, Nottoway, Orange, Page, Patrick, Petersburg City, Pittsylvania, Poquoson City, Portsmouth City, Powhatan, Prince Edward, Prince George, Prince William, Pulaski, Radford, Rappahannock, Richmond, Richmond City, Roanoke, Roanoke City, Rockbridge, Rockingham, Russell, Salem, Scott, Shenandoah, Smyth, Southampton, Spotsylvania, Stafford, Staunton City, Suffolk City, Surry, Sussex, Tazewell, Virginia Beach City, Warren, Washington, Waynesboro City, Westmoreland, Williamsburg City, Winchester City, Wise, Wythe, York, 2016. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 010-002-003 Dataset: Present population totals as provided by the FBI. See the technical documentation for information on the process used by the FBI in estimating totals. Shows arrests, by offense, state, county, jurisdiction, and suspect age, sex, and race. Data are from the Uniform Crime Reporting (UCR) Program, which is a nationwide, cooperative statistical effort of more than 17,000 city, university and college, county, state, tribal, and federal law enforcement agencies voluntarily reporting data on crimes brought to their attention. The UCR Program counts one arrest for each separate instance in which a person is arrested, cited, or summoned for an offense. Because a person may be arrested multiple times during the year, the UCR arrest figures do not reflect the number of individuals who have been arrested. Rather, the arrest data show the number of times that persons are arrested, as reported by law enforcement agencies to the UCR Program. The UCR system defines a "juvenile" as anyone under 18 years of age, regardless of state definitions. https://ucr.fbi.gov/word Category: Criminal Justice and Law Enforcement Subject: Population Source: Federal Bureau of Investigation The Federal Bureau of Investigations (FBI) is the principal investigative arm of the U.S. Department of Justice. The Uniform Crime Reporting (UCR) Program was conceived in 1929 by the International Association of Chiefs of Police to meet a need for reliable, uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics. A 5-year redesign effort to provide more comprehensive and detailed crime statistics resulted in the National Incident-Based Reporting System (NIBRS) which collects data on each reported crime incident. The UCR Program is currently being expanded to NIBRS. http://www.fbi.gov/
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,009 | 0,017 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,175 | 0,177 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».