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The current study applied the concept of country image to a context of bilateral relations for two post-Soviet states to examine the impact of a mega sport event on the image of the host country Russia.

Surveys were collected before and after the World Cup to assess any changes among Georgians with regard to their views on Russia and intentions to visit.

The results showed a significant change in Russia’s pre-perceived cognitive image related to reputation, respect and development, as well as the emotional aspect and overall country image after the mega sport event. Interestingly, the affective image of Russia carried more weight in shaping the overall country image compared to the cognitive aspects, suggesting the increasing importance of emotional perceptions over beliefs. However, despite these changes, the study found that mega sport events did not significantly moderate the association between country image and behavior intentions in the context of Russo-Georgian hostile bilateral relations.

This study is one of the first examinations of the impact of hosting mega sport events in countries with hostile bilateral ties. The findings support that mega sport events can be an effective mechanism to gain soft power in that such events can arouse changes in people’s emotions and feelings towards the host country, even for those living in a country with a hostile relationship with the host country. The scope of applicability of these findings can be extended to other contexts, including future hosts of mega sport events in their geo-political contexts.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

The purpose of this paper is to consider youth gangs and county lines with reference to the current drive for a public health response to these issues.

This viewpoint paper traces the development of gang and serious youth violence responses in England, exploring the shift from a punitive to safeguarding response to young people affected by these issues.

Drawing on the learning from both Scotland and the USA, this paper considers the relevance of a public health model to responding to youth gangs and county lines, highlighting the key facets of such an approach.

This paper provides a historical context to the issues surrounding previous responses to youth gangs and goes on to consider the practicalities and relevance of a public health model response.

Global evidence suggests that youth offending has reduced; however, this study aims to suggest a more complex picture, with youth crime potentially being displaced to the digital space. Historically, young people and crime have been synonymous with public spaces and being visible. A shift or expansion to online offending requires revision of how the justice and educational systems respond to youth offending.

A systematic literature review explored keywords related to age, digital offence or harm and criminal or harmful nature, using a search, appraisal, synthesis and analysis framework.

Three emergent areas of digital youth crime are discussed: digitally assisted crime, digitally dependent crime and digital harm.

The shift in youth offending requires response adjustment from prevention to detection. Opportunities may exist to disrupt or redirect youth before they offend. Further data specific to digital offending is needed. These findings seek to provide a possible direction for future research.

The concept of digital displacement of youth offending is progressively emerging. This paper examines types of offending categorised into three areas of interest.

This study examines the relationships between the age at which female juvenile offenders receive their first sentencing and individual risk factors, family risk factors, and race. The individual risk factors include dropping out of school, physical abuse, sexual abuse, prostitution, substance abuse, gang involvement, poverty, pregnancy, and the existence of co‐defendants. The family risk factors include parents’ marital status, familial criminal activity, education level of parents, and receipt of public assistance. The results showed individual risk factors to have a statistically significant relationship with the dependent variable, age at first sentencing. Family risk factors did not have a statistically significant relationship to the dependent variable. Socio‐demographic risk factors were found to be statistically significant only indirectly, through the individual risk factor scale.

The rates of offending and re-offending for young males are higher than any other population. Whilst the UK Ministry of Justice (2020) states that rehabilitation programmes should aim to build a positive identity, little is known about the subjective experiences of how this occurs. Various theories and models suggest that the development of a positive identity assists rehabilitation for young men with convictions (i.e. Johns et al., 2017). Therefore, the current study aimed to gather personal narratives from male, young offenders with the intention of understanding identity development.

Twelve interviews were conducted with young men with convictions aged between 18 and 25 years who had almost completed a rehabilitation process within the community. Narrative analysis was used to analyse the data. All were engaging with the rehabilitation service as a result of conviction for low to medium level offences, including burglary, harm of another person and drug related offences.

Three plots were identified which explain identity when committing offences: “The Powerless”, “The Feared” and “The Disconnected”. One plot was evident within the narratives which explained positive identity when rehabilitated: “The Connected”. The findings illustrate the importance of an approach which considers various aspects of a young offender’s life.

The current study further adds to knowledge base of young offender rehabilitation by providing a systemic understanding of how men with convictions’ identity develop pre- and post-rehabilitation. New implications for trauma informed practice are discussed.