The influence of offender and victim ethnicity on perceptions of crime severity and recommended punishment
Bibliographic record
Abstract
Crime severity has been found to be one of the best predictors of sentencing decisions (Darley, Carlsmith, & Robinson, 2000).There is however a dearth of research examining the effect of offender and victim ethnicity on perceptions of crime seriousness, and the few studies that do exist have produced equivocal findings.Some studies find an effect of victim ethnicity (e.g., Cohen-Raz, Bozna, & Glicksohn, 1997), some studies find no significant effects of offender nor victim ethnicity (e.g., Benjamin, 1989), and some studies only find effects under certain conditions, such as when the crime is of low seriousness (e.g., Herzog, 2003a).The present study was conducted in an attempt to clarify these convoluted findings by using measures of modern and oldfashioned prejudice.Whereas old-fashioned prejudice refers to the belief that an out group is in someway inferior, modern prejudice refers to the view that a minority group no longer faces discrimination or that the minority group is being "too pushy" when advocating for equal rights (McConahay, 1983).Using a sample of undergraduate psychology students, it was found that when the crime was perceived as being quite severe, harsher punishments were recommended for the offender.Further to this, participants scoring high in modern prejudice perceived crimes to be more severe and recommended longer sentences in certain offender-victim ethnicity conditions than participants scoring low in modern prejudice.However, contrary to the hypotheses, no significant differences were found between high and low old-fashioned prejudice participants.Perceived offender responsibility and stability were also found to affect perceptions of crime severity and recommended punishment.When an offence was described as being stable (i.e., the offender had committed similar crimes in the past), v 3.6 Hypothesis 2: For participants who score high in modern prejudice, crimes committed by an Aboriginal offender will be perceived to be more serious and recommended punishments will be longer than crimes committed by a non-Aboriginal offender.It is hypothesized that this effect will be particularly pronounced for interethnic offences in which the victim is Caucasian.It is also hypothesized that this effect will be more pronounced for crimes resulting in low and intermediate harm.....................................46 3.7 Hypothesis 3: For participants who score high in old-fashioned prejudice, crimes committed by an Aboriginal offender will be perceived to be more serious and recommended punishments will be longer than crimes committed by a non-Aboriginal offender, regardless of the amount of harm caused by the crime.It is also hypothesized that this effect will be more pronounced for interethnic offences in which the victim is Caucasian.........
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".