“Same crime, same sentence?” Disparities in laypersons’ sanctioning preferences for male and female offenders, and the link to respondent gender bias

Abstract This study examined whether offender gender was associated with disparities in sanctioning preferences, and if these disparities were linked to implicit or explicit gender-bias attitudes. Participants (N = 316, n = 126 male, n = 190 female) completed an anonymous survey, the Implicit Association Test (IAT), the Ambivalent Sexism Inventory (ASI), and were randomly assigned to vignettes followed by sanction options on four crimes; solicitation, theft, child sexual abuse (CSA) and homicide. Half received the vignettes featuring female offenders and the other half with male offenders. Overall, participants selected significantly harsher sanctions for male offenders for three of four crimes: solicitation (d = .45), theft (d = .25), and homicide (d = .61), with a ns difference for child sexual abuse (d = .03). There was no participant gender effect. There was a significant leniency effect towards women, except for CSA. Results indicate a small effect for explicit gender stereotype for only two of the four crimes, solicitation and CSA, and no effect of implicit gender stereotype. This study offers support for the “leniency effect” in relation to women who offend, although these biases may not greatly affect sentencing preferences.

The research literature appears to demonstrate that when partialling out other variables, women are sentenced significantly more leniently than men.This study seeks to investigate whether well validated explicit and implicit gender bias measures predict attitudes for preferred sanctioning severity towards men and women who commit identical crimes.Specifically, the following three questions will be examined: (1) Is greater leniency shown towards women who offend compared to men?
(2) Is greater leniency towards women shown by both male and female respondents?
(3) Which form of bias (implicit versus explicit) is more predictive of leniency towards women?

Participants
Participants comprised of a convenience sample of adults (18 years and over).Recruitment for this study was through email, social networking platforms, survey exchange sites (surveyswap.comand surveycircle.com),and Prolific (compensated, funded by the authors).A criterion for inclusion in this study was that participants lived in Ireland.A total of 452 participants responded with 316 (126 males, 190 females) fully completing the survey.Only fully completed survey responses were included in the analysis; 136 participants were excluded due to partial completion of the questionnaire.The age of participants ranged from 18 to 68 years of age (M = 35, SD = 11.57).

Implicit gender bias
The most well-known implicit measure is the IAT (Greenwald et al., 1998).Its claim is that it measures thoughts and feelings without the respondent required to explicitly state their views.Participants completed the five-step gender stereotype IAT (Greenwald et al., 1998), as used in previous research (Rudman et al., 2001;Rudman & Glick, 2001;Rudman & Kilianski, 2000).Participants distinguished between fifteen male names and female names by pressing right and left keys on the computer keyboard.In addition, they distinguished seven agentic words (e.g., independent, individualistic) and seven communal words (e.g., communal, connected).Participants responded to female names and agentic words (female + agency) with the right key and male names with the communal words (male + communal) with the left key; they then repeated the steps in reverse.The creation, cleaning, and scoring of the IAT was conducted with "Shinyapp" via "Iatgen" (Carpenter et al., 2019) following D-score algorithms (Greenwald & Farnham, 2000).IAT data were cleaned whereby individual trials over 10,000 milliseconds were deleted, as were any trials where more than 10% of the responses were under 300 milliseconds.A negative score indicated stereotypical associations (female and communal, male and agentic), whereas a positive difference score indicated non stereotypical associations (male and communal, female and agentic).The analyses revealed an acceptable internal consistency using a split-half procedure (Spearman-Brown correlation = .74).

Punitiveness towards male and female offenders
This study employed two groups of four hypothetical vignettes (Figure 1).Participants' were randomly assigned to either group A (n = 158) or group B (n = 158).The crime was described identically for both groups, except for the name and gender of the offender.Four offences with different levels of seriousness were used in the vignettes: solicitation, theft, child sexual abuse (CSA), and homicide.Participants selected their preferred sentencing option from 1 to 6 ("In your opinion, if found guilty what sentence would be most appropriate?") in response to the vignette from the column on the right.
This study was approved by the Research Ethics Committee of the researchers' university.Data was gathered online from February 2021 until June 2021.An anonymised computer survey link directed participants to Qualtrics, a secure survey platform.

Results
It was examined whether the dependent measure-length of preferred sentence-would vary with: (1) Gender of the offender, (2) Respondent gender and, (3) Implicit and explicit gender bias.To test each of these three questions a series of analyses was conducted: descriptive statistics; t-test to compare respondent mean scores; a mixed model ANOVA, to determine if leniency was shown to women and if this was by both male and female respondents; correlations to examine the relationships between variables; and a series of regression analysis to examine associations between the implicit and explicit measures on the outcomes.

Respondent gender effect
Respondent gender differences were examined on the IAT, ASI, and its two sub-factors: BS and HS.The effect size ranged from small to medium (Table 1).IAT scores for female respondents (M = −.174,SD = .32)showed a greater difference in gender bias than for male respondents (M = −.107,SD = .30).Male respondents scored higher on gender bias on explicit measures than did females.Table 2 displays respondent gender differences for the four crimes, with men showing moderate to high leniency towards female offenders for theft and homicide, respectively.
Table 1 highlights the correlation matrix for respondents by gender and the results highlighted female respondents had a strong positive correlation between BS with sentencing for CSA (.292) and solicitation (.214).These results indicate that women who scored higher on BS gave longer sentences to male offenders for CSA and solicitation.Men who gave longer sentences for CSA also gave longer sentences for theft and homicide.

Gender bias effects
Results of the correlation (Table A1) showed that the IAT had a slightly positive relationship between the total ASI score (r = .11,n = 314, p = <.05) and HS (r = .12,n = 314, p = .03).There was no significant relationship between the implicit measure and BS (r = .07,n = 317, p = .19)with John is a 32-year-old male who works as a childcare worker.John lives alone and is not in a relationship.John has been charged with three counts of sexually assaulting a 7-year-old girl in his care.
Jane is a 32-year-old female who works as a childcare worker.Jane lives alone and is not in a relationship.Jane has been charged with three counts of sexually assaulting a 7-year-old girl in her care.Susan is a 51-year-old woman who has struggled with mental health issues all her life.Susan presented to the local police station alleging she killed her husband with a knife.It emerged from the investigation that Susan stabbed her husband 11 times after he did not clean up the kitchen.
Sean is a 51-year-old man who has struggled with mental health issues all his life.Sean presented to the local police station alleging he killed his wife with a knife.It emerged from the investigation that Sean stabbed his wife 11 times after she did not clean up the kitchen.Note: Participants selected their preferred sentencing from 1 to 6 ("In your opinion, if found guilty what sentence would be most appropriate?").sentencing for any of the four offences.The ASI score showed a strong positive relationship with solicitation (r = .20,n = 316, p = .001)and child sexual abuse (r = .13,n = 316, p = .02).BS had a strong positive correlation with the sentencing of child sexual abuse (r = .16,n = 316, p = .005)and solicitation (r = .15,n = 316, p = .009).There was also a strong positive relationship between HS and sentencing for solicitation (r = .21,n = 316, p = .001).These results indicate that higher levels of explicit gender bias were associated with higher sentencing outcomes.

Discussion
The aim of this study was to explore whether greater leniency was shown towards women who offend compared to men, and if that was shown by both men and women respondents.The study also looked to examine if traditional implicit and explicit gender stereotype measures were predictive of leniency towards women and if so, which measures?Based on the analysis of this study the results demonstrate that there was a leniency effect towards women, except in relation to child sexual abuse.Homicide had the strongest relationship with gender bias, with men receiving significantly longer sentences.This is in line with previous research (Bailey et al., 2020;Beeby et al., 2020;Cassidy & Rydberg, 2020;Deering & Mellor, 2009;Fridel, 2019;Maher, 2021;Mellor & Deering, 2010;Pina-Sanchez & Harris, 2020;Rachlinski et al., 2009) which found that gender bias influences decision making and perception of risk.Comparable with Higgins and Ireland (2009) and Mellor and Deering (2010), this study found that there were no differences between the participants, as both men and women respondents demonstrated the same general biases in sentencing male and female offenders.Casey and O 'Connell (1999) and Forney and Lacy (2022) both argued that the type of crime is a far greater determinant of sentencing severity than is bias.
The implicit and explicit measures both indicated the presence of gender-stereotypical attitudes, with male participants demonstrating higher gender bias on the explicit measures.These concur with previous research findings: women's explicit gender attitudes are more egalitarian than men's (Glick & Fiske, 1996;Rudman et al., 2001).However, female participants showed slightly higher implicit gender bias in relation to female agency than male respondents; this did not relate to sentencing severity.The findings of this study indicate that higher scores on the ASI scale were associated with higher sentencing for men who commit homicide, and higher sentencing for women who commit solicitation.The results showed that there was no effect of implicit gender stereotype on any of the crimes.There was a small positive effect for the explicit gender stereotype measure on sentencing preferences for solicitation and child sexual abuse.Nosek and Smyth (2007) argue that the IAT measures a related but distinct construct from the multidimensional model of the ASI (Glick & Fiske, 1996).A critique of the IAT has been its strength in predicting behaviour and whether the measure can adequately predict constructs that have real world influence.Evidence shows that the IAT measures fluctuate between test and re-test and it has been suggested it measures "states rather than traits" (Brownstein et al., 2019).Some researchers posit that measures of explicit bias such as the ASI (Glick & Fiske, 1996) have more validity than measures of implicit bias.
Potentially, the benevolent sexism perspective implies a chronic female victim eliciting chivalry from men.In such a framing, women are perceived as weak, sensitive, and needing to be protected from themselves.Alternatively, hostile sexism offers the perspective that women who violate gender expectations are deficient and are in need of medicalisation.Therefore, the perception of agency for women tended to be diminished, regardless of whether respondents prescribed to a benevolent or hostile perspective of sexism.
This study has several limitations that should be considered when interpreting the results.Firstly, this study has a modest sample size that uses lay persons and not criminal justice officials who oversee sentencing.However, this study looked to explore and examine if gender bias explained the disparities that exist in relation to our perception of offending behaviour and its harm.Secondly, the results are from hypothetical rather than real world examples.A future study to explore sentencing disparities would benefit from recruiting judges and real world cases to explore the factors that determine and influence judges' decision making in relation to the sentencing of men and women who offend.Thirdly, there is an absence of socio-demographic information about the sample, and therefore it is difficult to establish that it is representative of the general population.

Conclusion
The current study challenges the assumption that the public are free from gender bias in relation to the criminal justice system.Results revealed that there are substantial variations of perception between men (perceived as agentic) and women (perceived as communal) who commit the same crime.These variations can be explained by both implicit and explicit bias, indicating that gender stereotype attitudes are pervasive.However, in relation to offending behaviour and sentencing the implicit gender stereotype measure had no effect and the explicit gender stereotype offered a small effect on two of the four crimes.These results provide an interesting addition to the study of leniency bias for sentencing preferences.Overall, this study has established a strong leniency bias, however, this bias is not explained by individual differences in measures of implicit and explicit bias.Further research to investigate the causal affect for such variations in sentencing would greatly benefit how and why there is a "leniency effect" towards women who offend.You are free to: Share -copy and redistribute the material in any medium or format.Adapt -remix, transform, and build upon the material for any purpose, even commercially.The licensor cannot revoke these freedoms as long as you follow the license terms.
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single mother of three who struggles with addiction issues.Mary grew up in foster care and left school at 16 years of age.Mary has been charged with 21 counts of theft.Martin is a single father of three who struggles with addiction issues.Martin grew up in foster care and left school at 16 years of age.Martin has been charged with 21 counts of theft.24-year-old male, with no previous criminal history.Paul has been charged with solicitation for the purpose of prostitution.Paula is a 24-year-old female, with no previous criminal history.Paula has been charged with solicitation for the purpose of prostitution.
Figure 1.Description of group A and group B vignettes that participants were assigned and sentencing length for the four crimes.

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Table 1 . Frequency, mean, standard deviation, and the intercorrelation for the implicit and explicit measures and the sentencing for the four offences, with respondent gender differences
-Note: *p < 0.05; **p < .01(2-tailed).Correlations displayed for women (n = 190) above the diagonal; correlations for men (n = 126) displayed below the diagonal.Abbreviations: IAT, Implicit Association Test d-score; ASI, Ambivalent Sexism Inventory Total score; BS, Benevolent Sexism; HS, Hostile Sexism; CSA, child sexual abuse.

Table 2 . Respondent gender difference and total mean, standard deviation, and effect size on crime sentencing for male and female offenders Male offenders
Note: *p < 0.05; **p < .001.Dependent variable: "In your opinion, if found guilty what sentence would be most appropriate?"(Scores 1 to 6).

Table 3 . Hierarchical Multiple Regression Analysis Summary Predicting Sentencing outcomes with respondent gender, offender gender, ASI and IAT scores Solicitation Theft CSA Homicide B SE B Beta sr Change in R 2 R 2 B SE Beta sr Change in R 2 B SE B Beta sr Change in R 2 R 2 B SE B Beta sr Change in R 2 R 2
Note: ASI = Ambivalent Sexism Inventory; IAT = Implicit Association Test; CSA = Child Sexual Abuse; *** p < .001,** p < .05