Montpellier - Environment, People and the Quality of Life

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        GEOG 2190        23/04/02

Montpellier: Environment, People and the Quality of Life

        Montpellier is a diverse and dynamic city that has experienced massive growth and change since the 1970s.  During this period the city has received massive inward investment, established itself as a European (if not global) technopole, completed a number of large scale architectural projects, carried out extensive suburban residential development and has experienced a three fold growth in its population.  As well as providing a thriving retail, commercial and tourist centre in the Languedoc-Rousillon region.  However nationally this region has continued to battle with high rates of unemployment as well as suffering other social problems such as high demands on housing provision and high crime rates.

        This project aims to discover what living in modern Montpellier is really like, by attempting to assess the quality of life.  I will firstly introduce the two types of quality of life indicators (hard and soft) and describe their benefits and disadvantages, as well as describing in detail the method used to carry out our assessment.  Two contrasting areas of the city were investigated and the second half of this report will describe these areas and detail our findings.  I will also compare the two areas and hopefully depict the diversity of the quality of life within Montpellier.  In addition to this I will critically assess the methodology we used in our enquiry and our adaptations to it.

        There are two ways of studying the quality of life in/of an area.  Firstly is by the use of hard indicators, usually from census data, such as unemployment, average income, car ownership, housing tenure and crime rates.  It is this sort of data that goes to make up many investigations on quality of life and deprivation.  The benefit of such indicators is that they are, on the whole, comparable on a time scale.  That is present data can be compared to data from ten years ago to analyse changes over time.  It can also allow greater breadth in an enquiry by making comparisons between other areas easy.  Another benefit is it is cheap.  Obtaining such information through raw data collection is a costly and time consuming process, and indeed can be an impossible task for one person.  However data quality can be inadequate, poorly documented, inaccurate or dated.  It also lacks flexibility and the depth provided by softer indicators, as well as assuming that quality of life is wholly based on tenure, unemployment etc.

        Soft indicators are usually primary sources of data and therefore lack the problems that secondary data can have such as being dated.  These soft indicators seek to identify and assess other aspects of an area that contribute to its quality.  Such indicators include amongst others, accessibility (particularly to health and education), level of service provision, traffic, air pollution and aesthetics.  These indicators provide a greater understanding of the quality of life in a particular area than census data can, but lack the convenience and ease of comparison and scope that comes with secondary data.  Another concern is that this data is subjective.  What one person thinks is a high level of traffic may be negligible to another and levels of aesthetics will be affected by tastes.  The full limitations of these indicators are examined later on in detail.

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        In order to carry out our assessment of the quality of life, based on such indicators, we adopted an assessment schedule developed by Duncan in 1997, as can be seen below in table 1.

Table 1.  Duncan’s assessment schedule

        Two areas of the city were chosen.  The first of these was a large residential complex called the Antigone.  Located in the heart of the city this development was designed by Ricardo Bofill in 1984 and was built on a 25-hectare site costing 200million francs to construct.  The Antigone’s location within the city can be seen in ...

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