Estimator Variables Impacting Eyewitness Identification in Criminal Justice System
Verified
Added on 2023/06/18
|4
|623
|219
AI Summary
This essay discusses the impact of estimator variables on eyewitness identification in the criminal justice system. It covers factors like race, weapon focus, trauma, and stress that affect eyewitness accuracy. The essay concludes that estimator variables cannot be controlled by the criminal justice system.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.
Psychology and criminal justice
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
TABLE OF CONTENT INTRODUCTION.................................................................................................................................3 MAINBODY.........................................................................................................................................3 CONCLUSION.....................................................................................................................................3 REFERENCES......................................................................................................................................4
INTRODUCTION Eyewitness identification is mainly an evidence which is being used as an important identification tool that is being received from the witness who had seen the whole event and can help out the court in order to testify the whole scenario. This is mainly a suspension and identification By a witness who had seen the offender committing crime. This mainly depend upon the estimator variables and system variables through which the accuracy of eyewitness can be controlled in criminal justice system(Benson, Masten, and Torgovitsky, 2020).This essaywillcoverthethreeestimatorvariablesthatmainlyimpacttheeyewitness identification. MAINBODY Estimator variablesare mainly those factors which cannot be controlled in criminal justice system as it used to cover all the basic factors like the distance at which the crime has taken place and the activities that has been addressed by the witness. This cover out thewitness, criminal event and the perpetratorwho were being involved and have seen the whole scenario of that event. This mainly covers all the complex factor which are like racethat identifies the accuracy of witness in order to identify the criminal matter, presence of weapon at the time of crime and the trauma and stressthat the witness has faced and experienced while seeing the act. Police cannot control the estimator variables as it is not being possible foranycriminaljusticesystemtoavoidtheestimatevariablestobeaddressed. The most important estimated variable that was being seen as race of eyewitness, as it is at time difficult to identify a strangers face from any other race in spite of identifying face of any stranger from their own race (Naz, and et. al., 2019). Other than this the most focused estimator variable is weapon focusas the presence of any kind of weapon used to draw attention towards it which mainly provides less reliable identification by the eyewitness (Drews, 2021). And lastly the trauma, stress and the fearthat used to arise at the time of seeing such situation used to create it more complex as these are mainly more focused estimator variables that are being analysed and cannot be controlled by the criminal justice system. All these help out to provide the fair and traceable opportunity to all the justice system in order to reach to all the records and the issues which are being laid in it.
CONCLUSION From this above essay it is concluded that eyewitness identification is mainly an evidence that is being taken by court from the witness who had testified the event and seen it from there bare eye. Estimator variable are mainly all such eyewitness accuracy that can affect the identification and cannot be maintained in control by criminal justice system. REFERENCES Drews, N., 2021. Picture Perfect: Reforming Law Enforcement Use of Image Editing in Eyewitness Identification. Geo. Wash. L. Rev., 89, p.429. Benson, D., Masten, M. and Torgovitsky, A., 2020. IVCRC: Stata module to implement the instrumental variables correlated random coefficients estimator. Naz, and et. al., 2019. Moderating and mediating role of renewable energy consumption, FDI inflows, and economic growth on carbon dioxide emissions: evidence from robust least square estimator. Environmental Science and Pollution Research, 26(3), pp.2806-2819.