Are juries fair? - WhatDoTheyKnow
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Are juries fair? Technical annex Cheryl Thomas Technical Annex to Ministry of Justice Research Series 1/10
Transcript of Are juries fair? - WhatDoTheyKnow
Are juries fair?
Technical annex
Cheryl Thomas
Technical Annex to Ministry of Justice Research Series 1/10
Are juries fair?
Technical annex
Cheryl Thomas
The report is available on the Ministry of Justice website:
www.justice.gov.uk/publications/research.htm
© Crown Copyright 2010
Extracts from this document may be reproduced for non-commercial purposes on
condition that the source is acknowledged.
First Published 2010
Contents
1. Case simulation jury verdict results (Nottingham and Winchester Crown Courts) 1
2. Equations to accompany appendix 2 (case simulation juror decision-making
data analysis) 3
3. Analytical model for not guilty pleas by offence type and defendant ethnicity 7
4. Defendant ethnicity by court (all charges) 9
5. Analytical model and output for analysis of impact of ethnicity on verdict (court
effects) 11
6. Jury conviction rates by defendant ethnicity: CREST data 2006-08 23
7. Jury conviction rate by offence type: CREST data 2006-08 25
8. Analytical model and output for conviction rate by offence type and defendant
ethnicity: CREST 2006-08 27
9. Jury conviction rates for specific offences: CREST 2006-08 31
10. Jury conviction rates by court (confined to courts where there was a minimum
of 1,000 jury verdicts by deliberation in 2006-08) 33
11. Total number of jury verdicts by offence in all Crown Courts combined (for
offences where a minimum of 300 jury verdicts were reached in 2006-08) 35
12. Relationship between multiple charges against a defendant and jury conviction
rates 37
13. Distribution of all hung juries by number of defendants and number of charges:
CREST 2006-08 39
14. Racial stereotyping results for jurors on all-White and racially mixed juries 41
15. Relationship between this report’s criminal offence categories for jury
conviction rates and criminal offence categories used in government statistics
for Crown Court conviction rates 45
1
1. Case simulation jury verdict results (Nottingham and Winchester Crown Courts)
Table TA1.1: All-White jury verdicts in case simulation at Nottingham Crown Court
Votes Defendant Victim Final verdict on ABH charge
Verdict type Guilty Not guilty
BME (Black) White Not guilty Unanimous 0 12
BME (Asian) White Not guilty Unanimous 0 11
BME (Black) White Not guilty Majority 2 10
BME (Asian) White Hung jury 5 7
BME (Black) BME (Black) Not guilty Unanimous 0 10
BME (Asian) BME (Asian) Hung jury 5 7
BME (Black) BME (Asian) Hung jury 5 7
BME (Asian) BME (Black) Hung jury 6 6
BME (Asian) BME (Black) Hung jury 6 5
BME (Black) BME (Asian) Hung jury 4 8
White BME (Black) Guilty Unanimous 12 0
White BME (Asian) Guilty Unanimous 12 0
White BME (Black) Hung jury 8 4
White BME (Black) Hung jury 7 5
White BME (Asian) Hung jury 6 6
White BME (Asian) Not guilty Unanimous 0 12
White White Not guilty Unanimous 0 12
White White Not guilty Unanimous 0 12 White White Not guilty Unanimous 0 11
White White Not guilty Majority 2 10
2
Table TA1.2: All-White jury verdicts in case simulation at Winchester Crown Court
Votes Defendant Victim Final verdict on ABH charge
Verdict type Guilty Not guilty
BME (Black) White Not guilty Unanimous 0 12
BME (Black) White Hung jury 4 5
BME (Asian) White Hung jury 5 7
BME (Black) BME (Black) Guilty Unanimous 12 0
BME (Asian) BME (Asian) Not guilty Unanimous 0 11
BME (Black) BME (Asian) Not guilty Unanimous 0 12
BME (Asian) BME (Asian) Not guilty Unanimous 0 12
BME (Black) BME (Asian) Hung jury 4 8
BME (Black) BME (Black) Hung jury 4 8
BME (Asian) BME (Black) Hung jury 6 6
BME (Asian) BME (Black) Hung jury 5 7
White BME (Asian) Not guilty Majority 1 11
White BME (Asian) Not guilty Majority 1 11
White BME (Asian) Hung jury 6 6
White BME (Black) Hung jury 9 3
White BME (Black) Hung jury 4 8
White BME (Black) Guilty Majority 10 1
White White Not guilty Majority 1 11
White White Hung jury 9 2
White White Hung jury 6 5
White White Hung jury 2 8
3
2. Equations to accompany appendix 2 (case simulation juror decision-making data analysis)
Equation TA2.1:
Equation TA2.2:
4
Equation TA2.3:
Equation TA2.4:
5
Equation TA2.5:
Equation TA2.6:
6
Equation TA2.7:
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3. Analytical model for not guilty pleas by offence type and defendant ethnicity
A multilevel binary logistic regression model was fitted, with binary pleas nested within trial to correctly control for clustering of pleas by trial. Table TA3.1 shows model estimates for each offence type (mean not guilty pleas). Defendant ethnicity, offence type and their interaction were included as fixed effects. Equation TA3.1 shows model output, including parameter estimates and their standard errors.
Table TA3.1: Mean estimates of not guilty pleas using the model in equation TA3.1
Blackstone’s criminal offence type White mean
BME mean
Unknown mean
Homicide & related offences .62 .83 .65 Non-fatal offences against the person .44 .59 .49 Sexual offences .48 .69 .52 Theft, handling stolen goods and related offences .34 .44 .37 Deception, fraud and blackmail .27 .34 .37 Falsification, forgery and counterfeiting .34 .24 .35 Damage to property .39 .52 .42 Offences affecting public order .31 .48 .36 Offences against administration of justice .41 .44 .38 Customs and excise offences .44 .67 .38 Offences related to drugs .23 .30 .27 Offences related to proceeds of criminal conduct .51 .54 .59
Table TA3.2: Mean not guilty values using raw CREST data (for comparison)
Blackstone’s criminal offence type White mean
BME mean
Unknown mean
Homicide & related offences .65 .88 .69 Non-fatal offences against the person .44 .61 .49 Sexual offences .47 .74 .53 Theft, handling stolen goods and related offences .32 .43 .35 Deception, fraud and blackmail .23 .31 .35 Falsification, forgery and counterfeiting .31 .21 .32 Damage to property .38 .52 .41 Offences affecting public order .29 .48 .33 Offences against administration of justice .40 .43 .36 Customs and excise offences .41 .71 .35 Offences related to drugs .20 .26 .23 Offences related to proceeds of criminal conduct .52 .56 .62
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Equation TA3.1: Multilevel binary logistic regression, modelling binary plea (not guilty vs. guilty) on the basis of defendant ethnicity, offence type and their interaction
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4. Defendant ethnicity by court (all charges)
Defendant ethnicity Crown Court White Black Asian Other Unknown
Total
AYLESBURY 1,327 144 199 77 1,377 3,124 BASILDON 4,128 461 76 93 1,710 6,468 BIRMINGHAM 9,826 4,211 4,005 1,277 2,958 22,277 BLACKFRIARS 3,006 2,790 495 1,277 857 8,425 BOLTON 7,183 267 935 258 442 9,085 BOURNEMOUTH 3,090 104 135 76 136 3,541 BRADFORD 3,519 176 1,286 226 3,550 8,757 BRISTOL 5,423 787 171 186 2,721 9,288 BURNLEY 2,837 11 741 17 212 3,818 CAMBRIDGE 3,326 173 50 122 392 4,063 CANTERBURY 3,713 289 154 84 1,044 5,284 CARDIFF 9,199 319 232 143 4,744 14,637 CARLISLE 3,907 55 2 0 667 4,631 CENTRAL CRIMINAL COURT 999 756 357 289 787 3,188 CHELMSFORD 4,397 346 116 237 1,779 6,875 CHESTER 9,004 129 69 90 957 10,249 CHICHESTER 1,917 112 23 24 147 2,223 COVENTRY 2,518 385 288 194 373 3,758 CROYDON 3,567 1,684 533 1,113 743 7,640 DERBY 6,363 361 370 216 643 7,953 DONCASTER 1,873 42 22 24 325 2,286 DURHAM 4,885 10 13 11 302 5,221 EXETER 3,188 64 16 5 711 3,984 GLOUCESTER 2,271 166 65 111 182 2,795 GREAT GRIMSBY 1,837 19 28 23 1,714 3,621 GUILDFORD 4,636 271 307 121 1,086 6,421 HARROW 3,397 2,918 1,160 645 1,080 9,200 INNER LONDON 3,341 5,116 620 1,219 1,059 11,355 IPSWICH 2,950 281 54 65 1,227 4,577 ISLEWORTH 3,032 1,748 1,746 683 653 7,862 KINGSTON-UPON-HULL 2,289 46 46 59 3,784 6,224 KINGSTON-UPON-THAMES 4,341 2,241 1,106 553 919 9,160 LEEDS 9,438 806 1,109 582 2,414 14,349 LEICESTER 5,598 488 1,248 323 788 8,445 LEWES 6,368 972 301 228 1,028 8,897 LINCOLN 1,273 9 14 12 2,202 3,510 LIVERPOOL 16,896 488 248 187 9,899 27,718 LUTON 4,090 926 772 318 743 6,849 MAIDSTONE 6,680 350 198 324 2,362 9,914 MANCHESTER (CROWN SQ) 6,140 1,272 1,057 720 1,805 10,994 MANCHESTER (MINSHULL ST) 13,087 675 1,191 224 2,469 17,646 MERTHYR TYDFIL 1,475 5 4 0 119 1,603 MIDDLESEX GUILDHALL 469 222 41 148 637 1,517 MOLD 5,791 51 16 49 452 6,359 NEWCASTLE-UPON-TYNE 11,202 91 124 138 5,480 17,035 NEWPORT (IOW) 1,107 14 7 10 74 1,212
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Defendant ethnicity Crown Court White Black Asian Other Unknown
Total
NORTHAMPTON 3,128 286 111 121 1,337 4,983 NORWICH 5,052 115 31 150 3,412 8,760 NOTTINGHAM 7,306 1,320 416 645 1,608 11,295 OXFORD 2,891 421 180 87 953 4,532 PETERBOROUGH 1,999 276 337 104 200 2,916 PLYMOUTH 2,756 38 5 76 345 3,220 PORTSMOUTH 3,578 128 32 37 652 4,427 PRESTON 12,690 112 859 105 1,323 15,089 READING 3,794 659 617 201 1,768 7,039 SALISBURY 470 27 0 9 113 619 SHEFFIELD 8,080 744 702 252 1,128 10,906 SHREWSBURY 1,821 48 69 17 486 2,441 SNARESBROOK 6,445 4,260 2,421 1,083 3,192 17,401 SOUTHAMPTON 3,851 398 146 154 1,225 5,774 SOUTHWARK 3,187 1,606 947 3,000 2,208 10,948 ST ALBANS 4,844 628 293 425 649 6,839 STAFFORD 3,845 152 246 46 525 4,814 STOKE-ON-TRENT 3,580 171 275 112 337 4,475 SWANSEA 6,922 161 33 83 428 7,627 SWINDON 1,225 103 36 41 646 2,051 TAUNTON 1,405 3 5 4 405 1,822 TEESSIDE 9,141 269 404 224 1,220 11,258 TRURO 1,427 39 0 53 1,545 3,064 WARWICK 2,688 301 224 195 384 3,792 WEYMOUTH & DORCESTER 785 6 22 2 70 885 WINCHESTER 2,910 257 34 160 1,347 4,708 WOLVERHAMPTON 5,663 1,028 1,016 489 1,037 9,233 WOOD GREEN 3,540 2,914 558 715 2,004 9,731 WOOLWICH 2,499 1,233 249 639 359 4,979 WORCESTER 3,172 160 60 58 1,934 5,384 YORK 6,363 17 60 55 124 6,619
TOTALS: 343,960 50,731 32,138 22,123 102,717 551,669
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5. Analytical model and output for analysis of impact of ethnicity on verdict (court effects)
Section 1 fits a model analysis to examine whether different court centres tend to be more or less likely to find non-White/BME defendants guilty compared to White defendants. The model looks at the likelihood of guilty versus not guilty verdicts on the basis of offence type (Blackstone’s), defendant ethnicity and court. The model was fitted using MLwiN. Sections 2, 3 and 4 provide an examination of the impact of the percentage of BME defendants at court and the ethnic composition of the court catchment area on verdicts for White and BME defendants.
Section 1: Ethnicity by court interactions Analysis modelled probability of a guilty verdict on the basis of offence type, binary ethnicity (with defendants with unknown ethnicity removed), court and the interaction between court and defendant ethnicity.
Offence type was entered as a main effect to attempt to control for differences being a function of a different breakdown of offences for different courts. Blackstone’s 12 categories were used, which while not particularly sophisticated does highlight marked differences in conviction rates by offence type. Court was included as both a main effect and interaction with binary ethnicity. A handful of courts were removed due to lack of data for BME defendants. In this instance simple binary ethnicity was used (White vs. non-White/BME), with ‘unknown’ removed. Ethnicity was included as a main effect and interaction term with court.
A multilevel binary logit model was fitted, with verdicts nested within cases. Specifying the hierarchical structure in the data was particularly important, given very strong evidence of clustering in verdict by case. The model equation is shown in equation TA5.1 below. Having fitted the model, the customised predictions function within MLwiN (Rasbash, Charlton & Jones, 2008) was used to obtain mean predicted responses (p(guilty verdict)) by simulation using the model, for each combination of court and ethnicity (table TA5.1).
The table also shows upper and lower bounds of the confidence intervals for the predictions. ‘Homicide & related offences’ was used as a reference offence type for the simulation. Three additional columns have been added to the table. The percentage change column aids identification of instances where courts were predicted to have particularly different mean values for White and BME defendants. The final two columns highlight the volume of data on which the model was based for each court and, significantly, the rarity of BME defendants in some courts.
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Table TA5.1: Simulated predictions for mean ‘guilty’ by court and ethnicity
White BME Court Mean Low High Mean Low High
% change White n BME n BME %
AYLESBURY 0.52 0.44 0.61 0.61 0.48 0.73 16.0 221 85 27.8 BASILDON 0.52 0.46 0.58 0.71 0.56 0.83 36.5 427 80 15.8 BIRMINGHAM 0.54 0.50 0.59 0.54 0.50 0.59 -0.2 1,246 1,484 54.4 BLACKFRIARS 0.46 0.40 0.53 0.56 0.51 0.61 22.6 379 822 68.4 BOLTON 0.46 0.39 0.53 0.47 0.35 0.60 3.0 462 130 22.0 BOURNEMOUTH 0.42 0.35 0.49 0.55 0.39 0.70 30.7 371 75 16.8 BRADFORD 0.56 0.49 0.62 0.60 0.51 0.70 8.3 409 171 29.5 BRISTOL 0.54 0.49 0.60 0.49 0.41 0.58 -8.7 755 222 22.7 BURNLEY 0.47 0.37 0.57 0.46 0.31 0.62 -2.7 172 88 33.8 CAMBRIDGE 0.59 0.52 0.66 0.47 0.32 0.63 -20.7 420 64 13.2 CANTERBURY 0.53 0.46 0.60 0.47 0.32 0.62 -10.4 461 74 13.8 CARDIFF 0.54 0.49 0.58 0.51 0.38 0.63 -5.1 1,077 76 6.6 CARLISLE 0.54 0.47 0.61 0.59 0.20 0.90 9.4 424 18 4.1 CENTRAL CRIMINAL COURT 0.56 0.48 0.63 0.57 0.52 0.63 3.0 320 528 62.3 CHELMSFORD 0.52 0.46 0.58 0.58 0.42 0.74 10.8 450 41 8.4 CHESTER 0.53 0.48 0.58 0.41 0.25 0.59 -22.5 856 48 5.3 CHICHESTER 0.58 0.48 0.67 0.35 0.13 0.62 -39.5 179 15 7.7 COVENTRY 0.61 0.53 0.70 0.57 0.45 0.69 -7.3 224 79 26.1 CROYDON 0.56 0.50 0.62 0.56 0.50 0.62 -0.2 490 567 53.6 DERBY 0.60 0.54 0.66 0.62 0.50 0.72 2.3 570 122 17.6 DONCASTER 0.55 0.44 0.66 0.40 0.06 0.84 -28.1 112 3 2.6 DURHAM 0.52 0.44 0.60 0.54 0.09 0.94 4.0 289 4 1.4 EXETER 0.64 0.57 0.70 0.74 0.27 0.98 16.4 501 5 1.0 GLOUCESTER 0.56 0.48 0.64 0.50 0.29 0.71 -11.2 315 32 9.2 GUILDFORD 0.57 0.51 0.62 0.42 0.29 0.55 -26.4 795 67 7.8 HARROW 0.49 0.42 0.57 0.60 0.54 0.64 20.4 318 871 73.3 INNER LONDON. 0.56 0.51 0.62 0.56 0.51 0.60 -0.9 580 1,169 66.8 IPSWICH 0.51 0.44 0.57 0.51 0.39 0.63 -0.1 419 102 19.6 ISLEWORTH 0.52 0.46 0.58 0.57 0.52 0.62 9.3 525 837 61.5 KINGSTON-UPON-HULL 0.51 0.40 0.63 0.48 0.23 0.75 -5.8 156 17 9.8
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White BME Court Mean Low High Mean Low High
% change White n BME n BME %
KINGSTON-UPON-THAMES 0.56 0.51 0.62 0.53 0.47 0.58 -6.2 670 725 52.0 LEEDS 0.55 0.50 0.61 0.59 0.50 0.68 5.9 735 177 19.4 LEICESTER 0.54 0.48 0.61 0.54 0.45 0.63 -0.6 476 235 33.1 LEWES 0.57 0.53 0.62 0.55 0.46 0.63 -4.9 1,208 180 13.0 LINCOLN 0.58 0.47 0.69 0.70 0.28 0.96 20.7 137 6 4.2 LIVERPOOL 0.51 0.47 0.55 0.54 0.43 0.64 4.8 1,918 159 7.7 LUTON 0.56 0.51 0.62 0.65 0.58 0.72 16.5 764 313 29.1 MAIDSTONE 0.58 0.54 0.63 0.63 0.51 0.74 7.9 945 149 13.6 MANCHESTER (CROWN SQ) 0.58 0.52 0.64 0.58 0.51 0.64 -0.6 513 427 45.4 MANCHESTER (MINSHULL ST) 0.48 0.43 0.53 0.48 0.39 0.58 -0.3 1,143 172 13.1 MIDDLESEX GUILDHALL 0.47 0.32 0.62 0.61 0.48 0.72 29.1 59 93 61.2 NEWCASTLE-UPON-TYNE 0.49 0.44 0.54 0.34 0.17 0.56 -29.1 880 39 4.2 NORTHAMPTON 0.59 0.52 0.67 0.53 0.38 0.67 -10.3 312 53 14.5 NORWICH 0.60 0.53 0.67 0.52 0.30 0.72 -14.0 405 50 11.0 NOTTINGHAM 0.56 0.51 0.62 0.63 0.54 0.71 12.5 763 181 19.2 OXFORD 0.53 0.47 0.60 0.65 0.52 0.77 21.3 457 100 18.0 PETERBOROUGH 0.53 0.45 0.61 0.45 0.34 0.57 -15.0 325 138 29.8 PLYMOUTH 0.64 0.56 0.72 0.50 0.23 0.77 -22.1 321 14 4.2 PORTSMOUTH 0.53 0.46 0.58 0.55 0.38 0.71 4.2 556 43 7.2 PRESTON 0.49 0.45 0.54 0.52 0.40 0.64 5.4 861 86 9.1 READING 0.54 0.48 0.60 0.56 0.48 0.64 4.5 566 217 27.7 SALISBURY 0.80 0.62 0.92 0.22 0.02 0.61 -72.8 51 10 16.4 SHEFFIELD 0.58 0.52 0.64 0.58 0.49 0.67 1.2 585 181 23.6 SHREWSBURY 0.47 0.37 0.57 0.46 0.24 0.69 -1.5 210 17 7.5 SNARESBROOK 0.54 0.49 0.59 0.55 0.51 0.59 2.6 1,101 1,391 55.8 SOUTHAMPTON 0.53 0.47 0.60 0.55 0.41 0.69 4.4 436 90 17.1 SOUTHWARK 0.54 0.48 0.61 0.52 0.47 0.57 -4.7 554 1,080 66.1 ST ALBANS 0.52 0.46 0.58 0.56 0.45 0.66 6.9 661 166 20.1 STAFFORD 0.50 0.43 0.57 0.66 0.48 0.81 33.4 367 54 12.8 STOKE-ON-TRENT 0.49 0.42 0.57 0.55 0.39 0.71 12.0 406 46 10.2 SWANSEA 0.49 0.44 0.54 0.47 0.24 0.71 -4.4 969 28 2.8
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White BME Court Mean Low High Mean Low High
% change White n BME n BME %
SWINDON 0.58 0.48 0.67 0.58 0.38 0.76 0.3 206 35 14.5 TAUNTON 0.55 0.46 0.63 0.49 0.14 0.84 -11.3 374 6 1.6 TEESSIDE 0.56 0.51 0.61 0.46 0.33 0.58 -18.2 1,025 89 8.0 WARWICK 0.52 0.43 0.61 0.58 0.44 0.71 11.7 203 91 31.0 WINCHESTER 0.49 0.42 0.56 0.47 0.29 0.64 -4.7 386 41 9.6 WOLVERHAMPTON 0.62 0.56 0.67 0.63 0.56 0.70 2.4 646 302 31.9 WOOD GREEN 0.57 0.51 0.63 0.49 0.44 0.55 -13.4 595 670 53.0 WOOLWICH 0.45 0.39 0.51 0.59 0.53 0.65 30.6 510 488 48.9 WORCESTER 0.55 0.47 0.63 0.30 0.15 0.49 -45.9 395 45 10.2 YORK 0.57 0.51 0.63 0.85 0.65 0.96 48.8 765 40 5.0
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There was some evidence of significant differences in verdicts by ethnicity of defendant between courts. For example, compared to the reference court (Liverpool), both Worcester and Salisbury appeared to be significantly less likely to find BME defendants guilty compared to White defendants. In contrast, again compared to Liverpool, York appeared to be significantly more likely to find BME defendants guilty compared to White defendants.
However, several notes of caution should be made here. Some differences, while significant, were based on relatively small numbers of observations. For example, while the BME by Salisbury interaction term was significant compared to the Liverpool reference category (testing the interaction term, 2
1 = 7.09, p = 0.01), it should be noted that there were only 61 defendants with ethnicity data for Salisbury, and of these only 10 were BME. Only very limited inferences can be made with this quantity of data. Those courts where significant differences were found also tended to have low numbers of jury verdicts on which to base the analysis, and these findings should not be considered conclusive in any way.
It should also be noted that, while the analysis was fairly complex, it only controlled for a limited number of variables. In addition to court, defendant ethnicity and their interaction, only offence type and clustering by case were accounted for. This leaves the possibility that differences between courts may be in part due to unobserved variables not included in analysis. For example, with respect to offence type, using the simple Blackstone’s categorisation will not account for variations within a Blackstone’s category.
Section 2: Ethnicity in the court catchment area Table TA5.2 shows percentage change (from table TA5.1) as well as percentage BME in the court catchment area. The percentage change column aids identification of instances where courts were predicted to have particularly different mean values for White and BME defendants. It shows percentage difference between guilty verdicts for White and BME defendants on the basis of the estimates in table TA5.1.
Table TA5.2: Percentage change (difference between White and BME verdicts) and percentage BME in court catchment area
Court BME catchment % change AYLESBURY 9.3 16.0 BASILDON 3.7 36.5 BIRMINGHAM 22.3 -0.2 BLACKFRIARS 33.2 22.6 BOLTON 6.2 3.0 BOURNEMOUTH 2.4 30.7 BRADFORD 14.2 8.3 BRISTOL 4.5 -8.7 BURNLEY 9.8 -2.7 CAMBRIDGE 4.4 -20.7 CANTERBURY 2.5 -10.4 CARDIFF 4.7 -5.1 CARLISLE 0.7 9.4 CENTRAL CRIMINAL COURT 27.0 3.0 CHELMSFORD 2.8 10.8 CHESTER 1.6 -22.5 CHICHESTER 2.0 -39.5 COVENTRY 13.2 -7.3 CROYDON 17.7 -0.2 DERBY 5.8 2.3
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Court BME catchment % change DONCASTER 1.8 -28.1 DURHAM 1.4 4.0 EXETER 1.2 16.4 GLOUCESTER 2.8 -11.2 GUILDFORD 4.7 -26.4 HARROW 37.4 20.4 INNER LONDON 23.4 -0.9 ISLEWORTH 32.5 9.3 KINGSTON-UPON-HULL 1.9 -5.8 KINGSTON-UPON-THAMES 12.5 -6.2 LEEDS 6.3 5.9 LEICESTER 14.8 -0.6 LEWES 2.4 -4.9 LINCOLN 1.5 20.7 LIVERPOOL 2.9 4.8 LUTON 12.0 16.5 MAIDSTONE 4.1 7.9 MANCHESTER (CROWN SQ) 9.3 -0.6 MANCHESTER (MINSHULL ST) 10.6 -0.3 MIDDLESEX GUILDHALL 28.9 29.1 NEWCASTLE-UPON-TYNE 2.9 -29.1 NORWICH 1.6 -14.0 NOTTINGHAM 6.5 12.5 OXFORD 5.0 21.3 PETERBOROUGH 5.1 -15.0 PLYMOUTH 1.4 -22.1 PORTSMOUTH 2.9 4.2 PRESTON 6.0 5.4 READING 10.0 4.5 SHEFFIELD 6.3 1.2 SHREWSBURY 3.0 -1.5 SNARESBROOK 30.4 2.6 SOUTHAMPTON 4.8 4.4 SOUTHWARK 33.5 -4.7 ST ALBANS 6.4 6.9 STAFFORD 1.9 33.4 STOKE-ON-TRENT 3.3 12.0 SWANSEA 1.7 -4.4 SWINDON 2.9 0.3 TAUNTON 1.2 -11.3 TEESSIDE 2.5 -18.2 WARWICK 4.8 11.7 WINCHESTER 2.8 -4.7 WOLVERHAMPTON 13.7 2.4 WOOD GREEN 29.5 -13.4 WOOLWICH 15.6 30.6 WORCESTER 2.0 -45.9 YORK 1.4 48.8
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A simple bivariate correlation indicated that there was no evidence of a relationship between ethnicity in the court catchment area population and the extent to which BME defendants were more/less likely than White defendants to be found guilty; correlation coefficient (Spearman’s) = 0.044, p = 0.72.
Section 3: Percentage BME in court Table TA5.3 shows percentage change (from table TA5.1) as well as percentage of BME defendants in each court (unknown ethnicity removed). Again, the percentage change column aids identification of instances where courts were predicted to have particularly different mean values for White and BME defendants. It shows percentage difference between guilty verdicts for White and BME defendants on the basis of the estimates in table TA5.1.
Table TA5.3: Percentage change (difference between White and BME verdicts) and percentage BME in court
Court % change White (n) BME (n) BME % AYLESBURY 16.0 221 85 27.8 BASILDON 36.5 427 80 15.8 BIRMINGHAM -0.2 1,246 1,484 54.4 BLACKFRIARS 22.6 379 822 68.4 BOLTON 3.0 462 130 22.0 BOURNEMOUTH 30.7 371 75 16.8 BRADFORD 8.3 409 171 29.5 BRISTOL -8.7 755 222 22.7 BURNLEY -2.7 172 88 33.8 CAMBRIDGE -20.7 420 64 13.2 CANTERBURY -10.4 461 74 13.8 CARDIFF -5.1 1,077 76 6.6 CARLISLE 9.4 424 18 4.1 CENTRAL CRIMINAL COURT 3.0 320 528 62.3 CHELMSFORD 10.8 450 41 8.4 CHESTER -22.5 856 48 5.3 CHICHESTER -39.5 179 15 7.7 COVENTRY -7.3 224 79 26.1 CROYDON -0.2 490 567 53.6 DERBY 2.3 570 122 17.6 DONCASTER -28.1 112 3 2.6 DURHAM 4.0 289 4 1.4 EXETER 16.4 501 5 1.0 GLOUCESTER -11.2 315 32 9.2 GUILDFORD -26.4 795 67 7.8 HARROW 20.4 318 871 73.3 INNER LONDON -0.9 580 1,169 66.8 IPSWICH -0.1 419 102 19.6 ISLEWORTH 9.3 525 837 61.5 KINGSTON-UPON-HULL -5.8 156 17 9.8 KINGSTON-UPON-THAMES -6.2 670 725 52.0 LEEDS 5.9 735 177 19.4 LEICESTER -0.6 476 235 33.1 LEWES -4.9 1,208 180 13.0 LINCOLN 20.7 137 6 4.2
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Court % change White (n) BME (n) BME % LIVERPOOL 4.8 1,918 159 7.7 LUTON 16.5 764 313 29.1 MAIDSTONE 7.9 945 149 13.6 MANCHESTER (CROWN SQ) -0.6 513 427 45.4 MANCHESTER (MINSHULL ST) -0.3 1,143 172 13.1 MIDDLESEX GUILDHALL 29.1 59 93 61.2 NEWCASTLE-UPON-TYNE -29.1 880 39 4.2 NORTHAMPTON -10.3 312 53 14.5 NORWICH -14.0 405 50 11.0 NOTTINGHAM 12.5 763 181 19.2 OXFORD 21.3 457 100 18.0 PETERBOROUGH -15.0 325 138 29.8 PLYMOUTH -22.1 321 14 4.2 PORTSMOUTH 4.2 556 43 7.2 PRESTON 5.4 861 86 9.1 READING 4.5 566 217 27.7 SALISBURY -72.8 51 10 16.4 SHEFFIELD 1.2 585 181 23.6 SHREWSBURY -1.5 210 17 7.5 SNARESBROOK 2.6 1,101 1,391 55.8 SOUTHAMPTON 4.4 436 90 17.1 SOUTHWARK -4.7 554 1,080 66.1 ST ALBANS 6.9 661 166 20.1 STAFFORD 33.4 367 54 12.8 STOKE-ON-TRENT 12 406 46 10.2 SWANSEA -4.4 969 28 2.8 SWINDON 0.3 206 35 14.5 TAUNTO -11.3 374 6 1.6 TEESSIDE -18.2 1,025 89 8.0 WARWICK 11.7 203 91 31.0 WINCHESTER -4.7 386 41 9.6 WOLVERHAMPTON 2.4 646 302 31.9 WOOD GREEN -13.4 595 670 53.0 WOOLWICH 30.6 510 488 48.9 WORCESTER -45.9 395 45 10.2 YORK 48.8 765 40 5.0
Section 4: Relationship between ethnicity in the court and catchment area
This section aims to examine whether BME defendants were more likely than White defendants to be found guilty where there was a larger discrepancy between BME representation among defendants at court and BME representation in the court catchment area population.
Table TA5.4 shows discrepancy between BME defendants in each court and BME representation in the catchment area. This is simply percentage BME in the catchment area (column B) divided by percentage BME defendants (column A). A value of 1 would indicate that the percentage of BME defendants and percentage BME in the catchment area were the same. Column C can be compared to the percentage change figure in column D, which is the
19
same as the percentage change in table TA5.1 above. It might be expected, for example, that BME defendants do increasingly worse than White defendants (higher values in column D) where BME defendants make up a large proportion of defendants in comparison to the make-up of the court catchment area population (higher values in column C).
Table TA5.4: Discrepancy in representation of BME defendants in courts compared to catchment areas (column C) and the extent to which BME defendants are more likely than White defendants to be found guilty (D)
Column A Column B Column C Column D Court % BME
defendant % BME in catchment
Col. B/Col. A % change
AYLESBURY 27.8 9.3 3.0 16.0 BASILDON 15.8 3.7 4.3 36.5 BIRMINGHAM 54.4 22.3 2.4 -0.2 BLACKFRIARS 68.4 33.2 2.1 22.6 BOLTON 22.0 6.2 3.5 3.0 BOURNEMOUTH 16.8 2.4 7.0 30.7 BRADFORD 29.5 14.2 2.1 8.3 BRISTOL 22.7 4.5 5.0 -8.7 BURNLEY 33.8 9.8 3.4 -2.7 CAMBRIDGE 13.2 4.4 3.0 -20.7 CANTERBURY 13.8 2.5 5.5 -10.4 CARDIFF 6.6 4.7 1.4 -5.1 CARLISLE 4.1 0.7 5.9 9.4 CENTRAL CRIMINAL COURT 62.3 27.0 2.3 3.0 CHELMSFORD 8.4 2.8 3.0 10.8 CHESTER 5.3 1.6 3.3 -22.5 CHICHESTER 7.7 2.0 3.9 -39.5 COVENTRY 26.1 13.2 2.0 -7.3 CROYDON 53.6 17.7 3.0 -0.2 DERBY 17.6 5.8 3.0 2.3 DONCASTER 2.6 1.8 1.4 -28.1 DURHAM 1.4 1.4 1.0 4.0 EXETER 1.0 1.2 0.8 16.4 GLOUCESTER 9.2 2.8 3.3 -11.2 GUILDFORD 7.8 4.7 1.7 -26.4 HARROW 73.3 37.4 2.0 20.4 INNER LONDON 66.8 23.4 2.9 -0.9 ISLEWORTH 61.5 32.5 1.9 9.3 KINGSTON-UPON-HULL 9.8 1.9 5.2 -5.8 KINGSTON-UPON-THAMES 52.0 12.5 4.2 -6.2 LEEDS 19.4 6.3 3.1 5.9 LEICESTER 33.1 14.8 2.2 -0.6 LEWES 13.0 2.4 5.4 -4.9 LINCOLN 4.2 1.5 2.8 20.7 LIVERPOOL 7.7 2.9 2.7 4.8 LUTON 29.1 12.0 2.4 16.5
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Column A Column B Column C Column D Court % BME
defendant % BME in catchment
Col. B/Col. A % change
MAIDSTONE 13.6 4.1 3.3 7.9 MANCHESTER (CROWN SQ) 45.4 9.3 4.9 -0.6 MANCHESTER (MINSHULL ST) 13.1 10.6 1.2 -0.3 MIDDLESEX GUILDHALL 61.2 28.9 2.1 29.1 NEWCASTLE-UPON-TYNE 4.2 2.9 1.4 -29.1 NORWICH 11.0 1.6 6.9 -14.0 NOTTINGHAM 19.2 6.5 3.0 12.5 OXFORD 18.0 5.0 3.6 21.3 PETERBOROUGH 29.8 5.1 5.8 -15.0 PLYMOUTH 4.2 1.4 3.0 -22.1 PORTSMOUTH 7.2 2.9 2.5 4.2 PRESTON 9.1 6.0 1.5 5.4 READING 27.7 10.0 2.8 4.5 SHEFFIELD 23.6 6.3 3.7 1.2 SHREWSBURY 7.5 3.0 2.5 -1.5 SNARESBROOK 55.8 30.4 1.8 2.6 SOUTHAMPTON 17.1 4.8 3.6 4.4 SOUTHWARK 66.1 33.5 2.0 -4.7 ST ALBANS 20.1 6.4 3.1 6.9 STAFFORD 12.8 1.9 6.7 33.4 STOKE-ON-TRENT 10.2 3.3 3.1 12.0 SWANSEA 2.8 1.7 1.6 -4.4 SWINDON 14.5 2.9 5.0 0.3 TAUNTON 1.6 1.2 1.3 -11.3 TEESSIDE 8.0 2.5 3.2 -18.2 WARWICK 31.0 4.8 6.5 11.7 WINCHESTER 9.6 2.8 3.4 -4.7 WOLVERHAMPTON 31.9 13.7 2.3 2.4 WOOD GREEN 53.0 29.5 1.8 -13.4 WOOLWICH 48.9 15.6 3.1 30.6 WORCESTER 10.2 2.0 5.1 -45.9 YORK 5.0 1.4 3.6 48.8
There was no evidence of BME defendants fairing increasingly worse than White defendants as BME defendants made up an increasingly disproportionate percentage at court compared to the catchment area. This is confirmed if a simple bivariate correlation is conducted; correlation coefficient (Spearman’s) = 0.027, p = 0.83.
21
Equation TA5.1:
22
23
6. Jury conviction rates by defendant ethnicity: CREST data 2006-08
This analysis examines whether BME defendants are more or less likely than White defendants to be found guilty by juries for all courts combined (ie, the proportion of all jury convictions by deliberation where the defendant is White and where the defendant is from a BME group). The analysis is conducted at the charge level, as juries convict on charges (ie, where a defendant is charged with multiple offences, juries will reach a verdict not on the defendant per se but on the individual charges against that defendant).
Table TA6.1: Jury conviction rates for defendants by ethnic group
Jury verdict Defendant ethnicity
Guilty Not guilty Total
24,987 14,839 39,826 White
62.7% 37.3% 100% 5,794 2,807 8,601
Black 67.4% 32.6% 100% 2,885 1,657 4,542
Asian 63.5% 36.5% 100% 2,059 1,146 3,205
Other 64.2% 35.8% 100% 8,035 4,242 12,277
Unknown 65.4% 34.6% 100%
43,760 24,691 68,451 Total:
63.9% 36.1% 100%
Table TA6.2: Jury conviction rates for White and BME defendants
Jury verdict Defendant ethnicity
Guilty Not guilty Total
24,987 14,839 39,826 White
62.7% 37.3% 100% 10,738 5,610 16,348
BME 65.7% 34.3% 100% 8,035 4,242 12,277
Unknown 65.4% 34.6% 100%
43,760 24,691 68,451 Total: 63.9% 36.1% 100%
Formatted Table
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25
7. Jury conviction rate by offence type: CREST data 2006-08
This analysis of CREST data examines the question: What offence types have the highest and lowest jury conviction rates where juries reach verdicts by deliberation? Offence type is defined using Blackstone’s 12 criminal offence types.
Jury verdict Blackstone’s criminal offence type
Not guilty Guilty Total
747 1,293 2,040 Homicide & related offences
36.6% 63.4% 100%
6,209 6,831 13,040 Non-fatal offences against the person 47.6% 52.4% 100%
7,803 12,729 20,532 Sexual offences
38% 62% 100%
3,511 8,357 11,868 Theft, handling stolen goods and related offences
29.6% 70.4% 100%
317 882 1,199 Deception, fraud and blackmail
26.4% 73.6% 100%
319 1,203 1,522 Falsification, forgery and counterfeiting 21% 79% 100%
391 471 862 Damage to property
45.4% 54.6% 100%
2,475 4,553 7,028 Offences affecting public order
35.2% 64.8% 100%
603 917 1,520 Offences against the administration of justice
39.7% 60.3% 100%
43 63 106 Offences under customs and excise legislation 40.6% 59.4% 100%
1,287 4,523 5,810 Offences related to drugs
22.2% 77.8% 100%
532 936 1,468 Offences related to proceeds of criminal conduct
36.2% 63.8% 100%
Unknown 454 1,002 1,456
24,691 43,760 68,451 Total:
36.1% 63.9% 100%
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8. Analytical model and output for conviction rate by offence type and defendant ethnicity: CREST 2006-08
A multilevel binary logistic regression model was fitted, with jury verdicts nested within trials to correctly control for clustering of verdicts by trial. The model includes offence type, defendant ethnicity and their interaction as fixed effects. The model was implemented using MLwiN. The offence type by ethnicity interaction term allows the impact of defendant ethnicity on jury verdict to vary by offence type. The model equation, including parameter estimates and standard errors is shown below in equation TA8.1. Total sample size is 66,995 jury verdicts (68,451 jury verdicts of guilty or not guilty minus 1,456 verdicts which were not classified into offence types).
Table TA8.1: Mean guilty jury verdicts by defendant ethnicity and offence type, simulated from the model in equation TA 8.1. (CI = confidence interval)
Blackstone’s criminal offence types Defendant ethnicity
Mean jury guilty
verdicts
CI low
CI high
White 0.568 0.534 0.602 BME 0.513 0.468 0.558 Homicide & related offences Unknown 0.588 0.536 0.638 White 0.498 0.483 0.512 BME 0.520 0.498 0.541 Non-fatal offences against the person Unknown 0.485 0.459 0.513 White 0.504 0.489 0.521 BME 0.495 0.467 0.523 Sexual offences Unknown 0.540 0.510 0.571 White 0.613 0.595 0.630 BME 0.637 0.615 0.659
Theft, handling stolen goods and related offences
Unknown 0.628 0.599 0.657 White 0.672 0.609 0.730 BME 0.733 0.670 0.790 Deception, fraud and blackmail Unknown 0.668 0.607 0.725 White 0.660 0.585 0.732 BME 0.745 0.681 0.804 Falsification, forgery and counterfeiting Unknown 0.659 0.603 0.714 White 0.550 0.507 0.594 BME 0.504 0.428 0.582 Damage to property Unknown 0.526 0.435 0.616 White 0.591 0.569 0.613 BME 0.644 0.618 0.669 Offences affecting public order Unknown 0.649 0.614 0.683 White 0.538 0.501 0.577 BME 0.541 0.483 0.599 Offences against the administration of justice Unknown 0.624 0.558 0.687 White 0.607 0.414 0.783 BME 0.822 0.468 0.985
Offences under customs and excise legislation
Unknown 0.594 0.406 0.763
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Blackstone’s criminal offence types Defendant ethnicity
Mean jury guilty
verdicts
CI low
CI high
White 0.706 0.681 0.730 BME 0.726 0.700 0.751 Offences related to drugs Unknown 0.684 0.644 0.721 White 0.687 0.631 0.742 BME 0.642 0.579 0.701
Offences related to proceeds of criminal conduct
Unknown 0.675 0.604 0.745
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Equation TA8.1: Multilevel binary logistic regression model equation, modelling binary verdict on the basis of offence type, defendant ethnicity and their interaction
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9. Jury conviction rates for specific offences: CREST 2006-08
Jury conviction rate for specific offences where a minimum 250 charges were decided by a jury in 2006-08
Offence Conviction rate % Not guilty Guilty Total number Making indecent photograph or pseudo-photograph of child 89.4 130 1,102 1,232 Death by dangerous driving 85.0 180 1,018 1,198 Having indecent photograph or pseudo-photograph of child 84.2 45 239 284 Possessing Class A controlled drug with intent to supply - Heroin 83.8 99 514 613 Possessing Class C controlled drug with intent to supply 82.0 115 523 638 Possessing Class A controlled drug with intent to supply - Cocaine 80.8 151 635 786 Obtaining a money transfer by deception 78.9 126 472 598 False accounting 76.4 143 463 606 Murder 76.3 185 596 781 Obtaining property by deception 76.1 103 328 431 Doing an act of cruelty to a child or young person under 16 years 74.5 72 210 282 Handling stolen goods 72.7 220 587 807 Doing act tending and intended to pervert course of public justice 72.7 97 258 355 Violent disorder 70.7 135 326 461 Proceeds of crime – possession of criminal property 69.9 101 234 335 Attempted robbery 69.8 177 410 587 Robbery 69.8 738 1,703 2,441 Having article with blade in public place 69.3 145 328 473 Indecent assault on male (under 16) 68.8 98 216 314 Committing gross indecency with female child 68.4 309 670 979 Burglary 68.1 396 832 1,222 Theft (from shop) 67.0 133 270 403 Exposure 66.6 124 247 371 Indecent assault on female under 16 66.2 472 925 1,419 Indecent assault on female under 14 65.5 999 1,894 2,893 Having offensive weapon 65.3 225 424 649 Theft 64.3 493 888 1,381
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Jury conviction rate for specific offences where a minimum 250 charges were decided by a jury in 2006-08
Offence Conviction rate % Not guilty Guilty Total number Indecent assault on female (16 or older) 64.2 130 233 363 Theft (by employee) 63.2 257 442 699 Indecent assault on male 62.1 167 274 441 Rape of female under 16 61.2 853 1,383 2,259 Affray 59.3 589 859 1,448 Sexual assault of female child under 13 58.2 413 576 989 Sexual activity with a female child under 16 57.0 293 388 681 Proceeds of crime (money laundering, converting criminal property) 56.7 158 207 365 Committing gross indecency with male child 55.8 121 153 274 False imprisonment 55.2 189 233 422 Assault occasioning actual bodily harm 54.4 2,346 2,795 5,141 Inflicting grievous bodily harm 53.1 513 580 1,093 Kidnapping 52.9 131 147 278 Wounding with intent to do grievous bodily harm 50.8 761 787 1,548 Unlawful wounding 48.6 537 508 1,045 Battery 47.7 149 136 285 Causing grievous bodily harm with intent to do GBH 47.6 406 369 775 Rape of female 16 or older 47.0 1,118 1,004 2,136 Attempted murder 46.7 171 150 321 Sexual assault on a female 46.1 893 765 1,658 Intimidating witness, juror or person assisting in investigation of offences 46.1 281 240 521 Common assault 40.9 655 454 1,109 Threatening to kill 35.7 236 131 367
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10. Jury conviction rates by court (confined to courts where there was a minimum of 1,000 jury verdicts by deliberation in 2006-08)
COURT Guilty verdicts
Not guilty verdicts Hung juries Total
Teesside 69.1 30.8 0.1 1,223 Harrow 68.3 31.2 0.4 1,351 Wolverhampton 67.8 31.8 0.4 1,049 Croydon 67.6 32.0 0.3 1,168 Maidstone 67.2 32.6 0.2 1,532 Lewes 66.6 31.8 1.6 1,606 Leeds 66.3 32.9 0.7 1,117 Nottingham 66.3 33.7 0.0 1,064 Manchester (Crown Square) 66.2 32.3 1.5 1,143 Isleworth 65.6 34.1 0.3 1,470 Inner London 65.4 34.4 0.3 1,918 Snaresbrook 64.7 34.4 0.9 2,939 Birmingham 64.3 35.3 0.4 3,071 Bristol 64.2 35.5 0.3 1,343 Woolwich 64.0 35.4 0.7 1,068 Kingston-Upon-Thames 63.8 35.5 0.7 1,524 Luton 63.3 36.5 0.2 1,225 Central Criminal Court 63.2 35.2 1.6 1,123 Blackfriars 62.7 36.8 0.5 1,291 Southwark 62.6 36.3 1.1 1,941 Guildford 62.5 36.3 1.3 1,092 Wood Green 62.2 37.7 0.1 1,561 Chester 60.9 38.6 0.5 1,133 Manchester (Minshull Street) 60.0 39.2 0.7 1,494 Liverpool 58.6 40.7 0.7 3,105 Cardiff 56.7 43.0 0.3 1,731 Newcastle-Upon-Tyne 56.0 44.0 0.0 1,278 Swansea 55.8 43.0 1.2 1,027 Preston 53.5 46.4 0.1 1,085
Formatted Table
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11. Total number of jury verdicts by offence in all Crown Courts combined (for offences where a minimum of 300 jury verdicts were reached in 2006-08)
Total number of jury verdicts Offence
5,141 Assault occasioning actual bodily harm 2,920 Indecent assault on female under 14 2,441 Robbery 2,136 Rape of a female aged 16 years or over 1,674 Rape of female under 16 1,667 Sexual assault on a female 1,548 Wounding with intent to do grievous bodily harm 1,448 Affray 1,419 Indecent assault on female under 16 1,232 Making indecent photograph or pseudo-photograph of child 1,222 Burglary 1,198 Dangerous driving 1,109 Common assault 1,096 Theft 1,093 Inflicting grievous bodily harm 1,045 Unlawful wounding 1,020 Sexual assault of female child under 13 979 Committing gross indecency with female child 807 Handling stolen goods 786 Possessing Class A controlled drug with intent to supply (Cocaine) 781 Murder 775 Causing grievous bodily harm with intent 699 Theft (by employee) 690 Sexual activity with a female child under 16 (offender 18 or over) 649 Having offensive weapon 638 Possessing Class C controlled drug with intent to supply 613 Possessing Class A controlled drug with intent to supply (Heroin) 606 False accounting 598 Obtaining a money transfer by deception 587 Attempted robbery 556 Sexual assault on a female by penetration 521 Intimidating witness, juror or person assisting in investigation 473 Having article with blade in public place 461 Violent disorder 442 Indecent assault on male (under 14) 431 Obtaining property by deception 422 False imprisonment 403 Theft (from shop) 376 Indecent assault on female (16 or older) 371 Exposure 367 Threatening to kill 365 Proceeds of crime - money laundering, converting criminal property
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Total number of jury verdicts Offence
355 Doing act tending and intended to pervert course of public justice 335 Proceeds of crime - possessing criminal property 327 Causing death by dangerous driving 321 Attempted murder 314 Indecent assault on male (under 16)
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12. Relationship between multiple charges against a defendant and jury conviction rates
This analysis looked at whether multiple charges against a defendant increase the likelihood that the defendant will be convicted by the jury on any charge. A conviction is recorded when the jury returned a guilty verdict on at least one of the charges against the defendant. The table below is the result of aggregating CREST data to the defendant level and relating the number of charges to “any guilty verdict” (ie, at least one). The table shows that the likelihood of a guilty verdict (on any charge) increases with the number of charges.
Table TA12.1: Guilty verdicts Number of charges
against defendant None Any (at least 1) Totals
5,080 3,412 8,492 1 59.8% 40.2% 100% 2,733 3,272 6,005 2 45.5% 54.5% 100%
881 2,178 3,059 3 28.8% 71.2% 100%
426 1,534 1,960 4 21.7% 78.3% 100%
158 817 975 5 16.2% 83.8% 100%
142 513 655 6 21.7% 78.3% 100%
76 298 374 7 20.3% 79.7% 100%
62 237 299 8 20.7% 79.3% 100%
32 147 179 9 17.9% 82.1% 100%
94 383 477 10-14 19.7% 80.3% 100%
35 198 233 15-19 15.0% 85.0% 100%
21 178 199 20+ 10.6% 89.4% 100%
9,740 13,167 22,907 TOTALS: 42.5% 57.5% 100%
Formatted Table
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13. Distribution of all hung juries by number of defendants and number of charges: CREST 2006-08
Type of trial Single defendant
Single charge
Multiple charges Multiple defendants
Jury verdicts by deliberation
Total number
Total with hung juries Hung
jury on only
charge
Hung jury on
all charges
Hung jury on at least 1 charge
but verdicts
on others
Hung jury on
all charges
Hung jury on at least 1 charge
but verdicts
on others
Cases 20,378 213 36 28 141 2 6
Verdicts 68,874 423 36 76 287 6 18
72% of hung juries (305 of 423) occur when a jury is presented with multiple charges, reaches verdicts on some charges but not all.
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14. Racial stereotyping results for jurors on all-White and racially mixed juries
Scores are on a 0 to 5 scale where 0 = highly unlikely to commit the crime in future and 5 = highly likely to commit the crime in future.
Defendant Asian Black White Offence Score
White jury
Mixed jury
White jury
Mixed jury
White jury
Mixed jury
Assault 0 9% 15% 23% 16% 13% 7% 1 21% 25% 23% 31% 22% 11% 2 29% 18% 26% 21% 24% 17% 3 35% 26% 19% 23% 19% 35% 4 3% 14% 7% 6% 16% 26% 5 3% 2% 2% 2% 6% 4%
Burglary 0 59% 51% 50% 52% 60% 48% 1 23% 31% 26% 27% 21% 31% 2 14% 14% 19% 12% 12% 12% 3 2% 3% 5% 8% 7% 8% 4 0% 0% 0% 1% 0% 1% 5 2% 1% 0% 0% 0% 0%
Drug possession 0 47% 31% 48% 42% 41% 28% 1 29% 28% 24% 27% 26% 23% 2 12% 20% 16% 15% 14% 25% 3 10% 14% 10% 11% 17% 17% 4 2% 6% 2% 2% 1% 5% 5 0% 1% 0% 3% 1% 2%
Rape 0 63% 58% 54% 67% 63% 58% 1 24% 26% 33% 20% 22% 23% 2 9% 11% 10% 7% 8% 12% 3 2% 2% 3% 5% 6% 6% 4 0% 2% 0% 0% 1% 1% 5 2% 1% 0% 1% 0% 0%
Benefit fraud 0 59% 41% 46% 38% 50% 42% 1 17% 30% 23% 35% 27% 23% 2 14% 16% 19% 15% 10% 19% 3 7% 10% 9% 9% 11% 13% 4 3% 2% 3% 3% 2% 3% 5 0% 1% 0% 0% 0% 0%
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Defendant Asian Black White Offence Score
White jury
Mixed jury
White jury
Mixed jury
White jury
Mixed jury
Racial abuse 0 41% 45% 43% 45% 24% 22% 1 31% 21% 28% 31% 28% 20% 2 9% 13% 19% 10% 13% 29% 3 16% 16% 5% 12% 20% 18% 4 0% 2% 5% 1% 13% 10% 5 3% 3% 0% 1% 2% 1%
Domestic violence 0 37% 37% 40% 34% 44% 25% 1 33% 23% 29% 30% 28% 25% 2 16% 19% 17% 22% 8% 23% 3 11% 15% 12% 10% 14% 22% 4 3% 4% 2% 2% 6% 3% 5 0% 2% 0% 2% 0% 0%
Stealing from employer 0 62% 44% 43% 49% 53% 46% 1 19% 25% 31% 30% 22% 26% 2 10% 17% 19% 12% 14% 18% 3 9% 12% 7% 9% 9% 8% 4 0% 1% 0% 0% 2% 2% 5 0% 1% 0% 0% 0% 0%
Causing disturbance in a 0 12% 13% 17% 23% 17% 8% public place 1 22% 24% 31% 33% 18% 13% 2 19% 22% 21% 19% 26% 15% 3 38% 27% 14% 14% 21% 30% 4 7% 8% 14% 11% 14% 26% 5 2% 6% 3% 0% 4% 8%
Selling illegal drugs 0 58% 45% 48% 54% 49% 43% 1 21% 26% 29% 25% 25% 26% 2 12% 19% 19% 11% 13% 20% 3 7% 6% 2% 9% 12% 7% 4 0% 3% 2% 1% 1% 3% 5 2% 1% 0% 1% 0% 1%
Having sex with an 0 57% 53% 43% 60% 56% 45% underage girl 1 24% 23% 35% 23% 22% 29% 2 10% 15% 10% 10% 13% 12% 3 9% 4% 10% 6% 8% 10% 4 0% 4% 2% 0% 0% 4% 5 0% 1% 0% 1% 1% 0%
43
Defendant Asian Black White Offence Score
White jury
Mixed jury
White jury
Mixed jury
White jury
Mixed jury
Handling stolen goods 0 48% 7% 39% 45% 46% 34% 1 26% 27% 28% 28% 24% 26% 2 9% 19% 19% 13% 15% 18% 3 12% 11% 12% 11% 12% 15% 4 2% 2% 2% 2% 2% 5% 5 3% 4% 0% 1% 1% 2%
44
45
15. Relationship between this report’s criminal offence categories for jury conviction rates and criminal offence categories used in government statistics for Crown Court conviction rates
Blackstone's 12 criminal offences categories (used in this report)
7 criminal offence categories used in government Crown
Court conviction rates
Sexual offences Sexual offences Drug offences Drug offences Homicide-related offences Violence against the person
Violence against the person Non-fatal offences against the person
Other offences
Theft and fraud Theft and handling stolen goods
Burglary and robbery
Theft and fraud Deception, fraud and blackmail
Other offences Falsification, forgery and counterfeiting Theft and fraud Damage to property Criminal damage Public order offences Other offences Offences related to the administration of justice Other offences Offences related to proceeds of criminal conduct Other offences Customs and excise offences Other offences
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