Contextual Effects On Youth Delinquency Criminology Essay

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This essay is going to critique 'City and/or Neighbourhood Determinants: Studying contextual effects on youth delinquency'. This essay will cover its aim, the theoretical approach used, its methodological choice and design, the data collected and used and its analysis. It is going to conclude by looking at the research outcome and its style and presentation.

The main aim of the research was to look at youth delinquency and see how the city, neighbourhood and individual influence it. The researchers looked at the data collected from 11 cities and analysed it to find a connection between youth delinquency and the city and neighbourhood levels. The research examined the extent to which determinants derived from social disorganisation theory at city and neighbourhood levels affect the youth delinquency over and above the influence of individual characteristics. The researchers were secondary analysts. They used economic income, ethnic heterogeneity, and family disruption as the variables in their research. The research concluded by finding that family disruption had an influence on delinquent behaviour while the other two variables did not. There exists previous research (Blackwell 1990; Peeples and Loeber 1994) on the above topic, but they only looked at each level individually, i.e. they only looked at city, neighbourhood or the individual level at any given time and never at all three simultaneously. This study was planning to integrate the three levels and analyse which phenomenon at which level affected youth delinquency. The research was undertaken to contribute to knowledge or understanding and to the development of a particular area of theory, in this case, social disorganisation theory focusing on the areas of youth delinquency and the influence of ecological contents.

The researchers in this study have gone on to base their research analysis on positivistic framework and the use of quantitative data. Positivism is the branch of sociology which believes that the social world can be seen in an objective way and it is possible to count observable social facts and produce statistics. Positivistic methodology requires looking for correlations between different social facts and involves searching for connections between these facts. If there was a strong correlation, then one may suggest that one of the phenomenons was responsible for the other. A similar connotation seems to be indicated in this study. Positivists are after a universal law of human behaviour and the data is used to generalise human behaviour. They use multivariate analysis to establish connections between two or more variables as is done in this research study about youth delinquency. Robson (2002) rejects the positivistic and quantitative view as a basis of real world research. According to Robson (2002), reality can only be subjective and not objective. He says it is wrong and unjustifiable to place emphasis on quantitative measurement as it cannot capture the real meaning of social behaviour. He advises the use of 'realism', a model of scientific explanation that avoids both positivism and relativism for real world research.

They base their hypothesis and research on social disorganisation theory, which was developed by Shaw and Mckay (1969). This theory links high crime rates to a neighbourhood and cities ecological characteristics. Youths from disadvantaged neighbourhoods were participants in a subculture in which delinquency was the approved behaviour and that deviant behaviour was acquired in a social and cultural setting through a process of interaction. The study cites previous work (Peeples and Loeber 1994; Sampson et al 1997) undertaken by other researchers using the same theoretical framework for their research at the neighbourhood or city levels. The authors use this to justify the use of the same theoretical framework for their research.

The research uses surveys and statistics and is hence quantitative in nature. It uses multivariate analysis in the study. It uses three variables, economic income, ethnic heterogeneity and family disruption. The study states that neither economic income nor ethnic heterogeneity has an effect on youth delinquency. It states that youths from a single parent family are more likely to be delinquent. The study does not give us any indication to the validity of the relationship between the variables. It does not take steps to minimize false positive and false negatives or it fails to tell us that it has done so. It neglects to inform us as to whether ethnic heterogeneity and economic income had an effect on family disruption. They were limited to the three variables or concepts because the data they could viably extract had the above three variables as the only uniform data set. The data they analysed were surveys taken from eleven cities in the Netherlands. These cities had conducted a youth survey which questioned adolescents who were 12-17 years old on their behaviour (delinquency, drinking, drug use and so on), home situation, relations with their parents, guardians and peers, and their background characteristics (age, ethnicity, gender etc). One of the main faults in their data as indicated by the study was that the data was not uniform. The data collection and sampling methods used by the cities were different for different cities. Some cities sampled all its youth, others took just the ones in schools and so on. The researchers spin this into a positive light saying that the non-uniformity led to adolescents in a wide range of areas being included in the research. It is mentioned in the study that they used only the data which was uniformly collected and sampled by all the eleven cities. It may be due to the lack of uniform data that they were not able to include any further concepts or variables in their research, thus stifling its findings and questioning its authenticity.

The researches have taken on the roles of analysts of previous data and have resorted to content analysis for this study. Content analysis looks at various documents and data and quantifies them in terms of usable data. The advantages of content analysis are - it is a very objective and transparent research method. It allows certain amount of longitudinal analysis with ease. It is an unobtrusive method (term devised by Webb et al, 1966), the participants do not have to take the researcher into account and is thus a non-reactive method (the participants do not react to the presence of the researcher and do not give information they think that the researcher wants to hear). It is a flexible method and can be applied to a wide variety of data and information. It allows information to be generated about various social groups that are difficult to gain access to. Content analysis does however have quite a few disadvantages - the potential for invalid conjectures being made gets magnified. It can only be as good as the documents the researcher works on. It holds good in this particular research study as the uniformity of the data is called into question. It is difficult to ascertain the cause or the reason for particular theories through content analysis. It may accused of being atheoretical. Problems may arise due to the differences between the aim of the document and the aim of researcher (Bryman 2001, pg 195). Other issues critics (May, 2004) bring up tend to stem from how documents are used rather than using them in the first place. Mistakes in research can be made due to selective reading of documents; the documents themselves may be selective. What people decide to record, to leave in or take out is itself informed and influenced by various social, political and economic factors. Thus documents are not just neutral artefacts from the past (May 2004, pg 80).

The sample populations were 12-17 year old adolescents. Neighbourhoods were identified by postcodes. The researchers controlled age, gender, and ethnicity of the sample population. Access was relatively easy to achieve as it was public data (based on the Dutch Standard Youth Monitor). As we do not have any information on the original data used, we cannot comment on the ethical or legality of the issue nor can we debate about the questionnaire, the nature of the questions asked and its phrasing. All we know about it is that it is based on the Dutch Standard Youth Monitor. Thus the validity and reliability of this research was limited due to the fact that the content of the original data is unknown and is therefore ambiguous on ethical and legal grounds.

In this research, the researchers undertake secondary analysis. They do not generate any of their own data but look at the data collected by other researchers and institutions. In this case, the national surveys in the Netherlands. The advantages of secondary analysis are that it saves on cost and time. It offers 'good quality' data for very little time and less amount of resources than if the data was to be collected by the researcher. The samples are usually widely varied. There is opportunity for longitudinal analysis. There can be the opportunity to study a wide variety and large quantity of subgroups. There is the opportunity for cross-cultural analysis as secondary analysis provides a large data set which can be used for cross cultural research. Usually in research, data collection takes up a lot of the time and very little is given for its analysis. This is not the case in secondary analysis as the data already exists. Hence there is more time for data analysis. Reanalysis of the data may bring about new interpretations or theories that may have been missed during the original research project. (Bryman 2001, pg 202). Secondary analysis however does face some substantial limitations. Firstly, the lack of familiarity of data is a substantial hindrance to the secondary analyst. Many of the data sets analysed will contain large amounts of data and variables. Thus it can be quite daunting for the researcher to familiarise oneself with the large and complex data sets. Secondly, the researcher has no control over the data quality. Particularly in this research as the data was not uniform. Thirdly, the absence of key variables is a key limitation in secondary analysis. As it involves the analysis of another researcher's data which was created for their own purposes, it may be that one or more key variables for the research may be missing (Bryman 2001). This is demonstrated in this study about youth delinquency as the researchers were limited to just three variables due to the lack of others. If the researchers collected primary data themselves, this could have been minimised.

The researchers use statistics that include correlation, variation and deviance. The formula used in statistics and for determining the results is clearly given (pg 448, footnote 5). The researchers could have taken a more qualitative or triangulative approach since they are dealing with juvenile delinquency which deals with behaviour (Robson, 2002). Their data calculation is mentioned. The concepts and articles used within the study such as economic status, ethnic heterogeneity and family disruption clearly defined. Although the study does at times fail to explain terms such as 'contextual disadvantage'.

The researchers looked at survey data. The disadvantages of it are that it tends to give the effect of casual relations between variables which is not applicable to human action. Two variables may be associated, but this does not mean that one variable causes a change in the other which may have led to false positive and false negatives. This is not adequately accounted for by the research. This could be the reason as to why they found a connection between single parents and delinquency while Peeples and Loeber (1994) did not. Secondly, surveys usually restrict the ways people are allowed to answer; it becomes inevitable that the researcher usually hears what he or she wants to hear and the theories usually proven. Thirdly, the response rates may be low, they cannot collect additional data, and there is a higher risk of missing data and so on. It however does have some advantages, mainly due to the fact that a large area of respondents can be covered (11 cities in this case), and is relatively cheap and easier than qualitative analysis (May 2004, pg 112). This could be a reason as to why the researchers chose such a method.

One of the primary sources of data the researchers look at is official statistics. There are many disadvantages to using official statistics. Firstly, there is the type of official data being used. Secondly, official statistics vary greatly in terms of their accuracy. Some such as the birth rate may be very highly accurate, whereas others such as with crime statistics may be off target to a great extent (May, 2004). The compilation of official statistics will also affect its analysis. The researchers in this study of youth delinquency take official statistics to be objective indicators of the phenomenon to which they refer, which leads us back to the positivistic school of thought. Thirdly, the aim of the official statistics would have been different to that of the researchers. As May says, 'One of the main drawbacks of official data is that they help to generate myths and propagate government propaganda by reflecting power relations and ideologies within society.' (May 2004, pg 83)

The study concluded that differences in youth delinquency rates between cities and between neighbourhoods cannot be attributed to the composition of the population. It found that the more disadvantaged a city or neighbourhood the more likely its adolescents will show delinquent behaviour. It also concluded that higher the percentage of single parent families, the higher the delinquent rate is going to be. These are in line with their starting theory and meet their expectations with the demographic results, i.e. older adolescents rather than younger ones are more likely to commit criminal acts or resort to delinquent behaviour, boys rather than girls are more likely to show delinquent behaviour and so on. The study did however bring up some unlikely results which were not predicted or expected by the researchers. Neither the mean income level nor the percentage of ethnic minorities in the city or neighbourhood affected the delinquency behaviour of adolescents. This is quite surprising considering that previous research (Peeples and Loeber 1994) has shown the opposite, i.e. the percentage of ethnic minorities in a city or neighbourhood does affect delinquency (Blom et al. 2005). Research undertaken by Peeples and Loeber (1994) found that single parent status was not relevant or indeed related to delinquent behaviour. It also found that the percentages of ethnic minorities do affect youth delinquency. The contradicting results could be explained by the fact that they had to use non-uniform data and were limited to specific data sets. The conclusions may have been different if they looked at all the data. Controversially, one can say that they arrived at this result because they looked at all three levels, i.e. city, neighbourhood and the individual while previous research did not.

The research article was laid out in an easy to read manner, is well written and has a clear script. It gives evidence of previous research in the field and even mentions a few drawbacks the researchers faced. Thus in this essay I have critiqued the above research study on its aims, theoretical basis, methodology, analysis of data, it design and style of presentation. Overall, it is a well thought out project giving a good insight into youth delinquency and social disorganisation theory.

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