What is he best known for?
The fields of study he is best known for:
- Law
- Statistics
- Criminology
His main research concerns Criminology, Crime prevention, Trajectory analysis, Problem-oriented policing and Social psychology.
His Criminology research includes themes of Law and Unit of analysis.
The Crime prevention study combines topics in areas such as Cultural criminology, Routine activity theory, Perception and Crime control.
His Problem-oriented policing research includes elements of Empirical evidence and Evidence-based policing.
His biological study spans a wide range of topics, including Intervention, Internal validity and Police legitimacy.
His studies in Crime displacement integrate themes in fields like Psychological intervention and Control.
His most cited work include:
- General deterrent effects of police patrol in crime “hot spots”: A randomized, controlled trial (707 citations)
- What Can Police Do to Reduce Crime, Disorder, and Fear? (576 citations)
- TRAJECTORIES OF CRIME AT PLACES: A LONGITUDINAL STUDY OF STREET SEGMENTS IN THE CITY OF SEATTLE* (543 citations)
What are the main themes of his work throughout his whole career to date?
David Weisburd spends much of his time researching Criminology, Crime prevention, Criminal justice, Social psychology and Psychological intervention.
His Criminology study combines topics in areas such as Law and Terrorism.
His study in Unit of analysis extends to Crime prevention with its themes.
His research is interdisciplinary, bridging the disciplines of Justice and Criminal justice.
His Social psychology study incorporates themes from Procedural justice and Police legitimacy.
His Psychological intervention study frequently draws connections to other fields, such as Social control.
He most often published in these fields:
- Criminology (72.04%)
- Crime prevention (23.49%)
- Criminal justice (17.45%)
What were the highlights of his more recent work (between 2017-2021)?
- Criminology (72.04%)
- Crime prevention (23.49%)
- Mental health (3.80%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Criminology, Crime prevention, Mental health, Collective efficacy and Prison.
The study incorporates disciplines such as Perception and Terrorism in addition to Criminology.
His Crime prevention study combines topics from a wide range of disciplines, such as Action, As is, Implicit bias, Transportation security administration and Scientific evidence.
His study in Mental health is interdisciplinary in nature, drawing from both Occupational safety and health and Depression.
His Collective efficacy research is multidisciplinary, incorporating perspectives in Psychological intervention, Survey data collection, Public health and Environmental health.
His Prison research integrates issues from Rehabilitation, Service and Recidivism.
Between 2017 and 2021, his most popular works were:
- Focused Deterrence Strategies and Crime Control (75 citations)
- Mean Streets and Mental Health: Depression and Post-Traumatic Stress Disorder at Crime Hot Spots. (30 citations)
- Mean Streets and Mental Health: Depression and Post-Traumatic Stress Disorder at Crime Hot Spots. (30 citations)
In his most recent research, the most cited papers focused on:
- Law
- Statistics
- Social science
David Weisburd mainly focuses on Criminology, Procedural justice, Collective efficacy, Mental health and Hot spot.
His work carried out in the field of Criminology brings together such families of science as Internal validity and External validity.
His studies deal with areas such as Replication, Criminal justice, Relevance, Social system and Enthusiasm as well as Procedural justice.
His Collective efficacy research incorporates elements of Fear of crime, Survey data collection, Intervention, Control and Collective action.
His Mental health research is multidisciplinary, relying on both Health equity and Environmental health.
He interconnects Crime prevention, Deterrence, Gang violence and Crime control in the investigation of issues within Problem-oriented policing.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
