“An individual’s level of personal well-being is strongly related to the level of wealth of the household in which they live”

“Relationship between Wealth, Income and Personal Well-being, July 2011 to June 2012”

Summary
This article uses data from the Wealth and Assets Survey (WAS) for July 2011 to June 2012
which, for the first time, included measures of personal well-being. It describes the results of
regression analysis considering the relationships between the total wealth or total income of
the households in which individuals live and their personal well-being. Regression analysis is
a statistical technique which was used to analyse variation in well-being outcomes by specific
characteristics and circumstances of individuals while holding all other characteristics equal.
This allows for a better understanding of what matters most to an individual’s personal well-being
compared to analysis when different factors are considered separately.
Main points
• An individual’s level of personal well-being is strongly related to the level of wealth of the
household in which they live. Life satisfaction, sense of worth and happiness are higher, and
anxiety less, as the level of household wealth increases.
• The levels of household income are less strongly related, with relationships found only with life
satisfaction and sense of worth.
• The net financial wealth of the household appears to be the type of wealth most strongly
associated with personal well-being. In particular, life satisfaction will be higher in households
with greater net financial wealth.
• Levels of property wealth and private pension wealth were not found to be related levels of
personal well-being.

Source

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World Values Survey International Open Seminar

wvshome

 

 

The “World Values ​​Survey International Open Seminar” will be held at the University of Almería on the 24th and 25th of November 2014. This conference is organized by the Department of Sociology and marks the release of the sixth wave of the World Values Survey (http://www.worldvaluessurvey.org). The conference will feature published papers and current research using this survey.

Interest in the World Values ​​Survey is not new in the ​​Sociology Department at the University of Almería. Encouraged by the Department chair, Professor Gonzalo Herranz Rafael, many in the department (including Pilar Rodríguez Martínez, Juan Sebastián Fernández Prados and Juan Carlos Checa Olmos) have been visiting scholars the University of Michigan, specifically the Institute for Social Research, hosted by Ronald Inglehart. Over the years, professors in the department have started using the World Values ​​Survey (WVS) both in their teaching and in their research as it is one of the best global surveys on changes in values ​​and its impact on social and political life. The WVS is based on nationally representative surveys in more than 100 countries containing almost 90percent of the world’s population, thus allowing cross-country comparisons. There have been six waves of surveys (from 1981 to 2014) which make longitudinal analyses possible.  Furthermore, by making the data freely downloadable, the organization behind the WVS allows researchers to work at no extra cost.

Like the World Values ​​Survey, this seminar is open and dynamic. It starts with a basic program which is available on this website but also we open the seminar to other proposals focused on the WVS.

Almería (Spain), 24-25 Nov 2014

(Deadline: Abstracts on 20th October 2014. Full manuscripts on 14th November 2014)

http://congresos.ual.es/emv2014/

Organized by:
Área de Sociologia
Universidad de Almería

Example of urban mapping research project

Title: Mapping social diversity
Phase one involved demographic mapping which would inform the survey in phase two, and then in-depth interviews as part of Project B. Using census data (UK 2001, Poland 2002), the residential distribution of people in terms of demographic characteristics was mapped in two cities: Leeds (UK) and Warsaw (Poland). Variables were selected to represent the key social dimensions of difference: demographic, socio-economic, ethnic and disability. A standard cluster analysis using a k-means algorithm was implemented for each city separately -for ‘Community Areas’ in Leeds and ‘Urban Regions’ in Warsaw.Graph 1. Cluster classification of Community Areas in LeedsGraph 2. Cluster classification of Urban Regions in Warsaw

cluster maps

Typologies of communities (‘diversity clusters’) were produced using the census data. These clusters varied in terms of wider diversity patterns, but that were internally homogenous. So the aim of the analysis was to reduce the internal variability while increasing the external variability between the types of communities. The mapping exercise has shown that patterns of residential segregation and mix in the two cities are different. Consequently, in different neighbourhoods there exist different opportunities to have contact with people who are different in terms of age, ethnicity, religion/belief, disability and socio-economic status.A comprehensive description of the mapping excercise and more details on the clusters are available in this working paper: click here Survey on attitudes, prejudice and discrimination In phase two we used the diversity clusters to produce a stratified survey sample. A large scale survey was completed by a professional surveying company. The total sample size for the survey was approximately 1500 interviews in each city (3000 in total). The survey examined (a) whether spatial proximity generates ‘meaningful contact’ among diverse social groups, (b) whether it generates respect and understanding regarding people who are different, and (c) which places of encounter constitute sites that can facilitate improved forms of intergroup relations.We intend to explain the variation in attitudes revealed in the survey using both individual attributes and the independent influence of living in particular diversity clusters. The results of the survey will be reported later in 2012/2013.

 In phase two we used the diversity clusters to produce a stratified survey sample. A large scale survey was completed by a professional surveying company. The total sample size for the survey was approximately 1500 interviews in each city (3000 in total). The survey examined (a) whether spatial proximity generates ‘meaningful contact’ among diverse social groups, (b) whether it generates respect and understanding regarding people who are different, and (c) which places of encounter constitute sites that can facilitate improved forms of intergroup relations.

We intend to explain the variation in attitudes revealed in the survey using both individual attributes and the independent influence of living in particular diversity clusters. The results of the survey will be reported later in 2012/2013.

Source: http://livedifference.group.shef.ac.uk/?page_id=105

Are you “resources” or “feeling” researcher? #understandingresearchphilosophies

As researcher you are creating new knowledge. But, what is or not knowledge for you? Two main views may be adopted.

(1) The researcher who concerns on numbers and countable elements: “resources” researcher

(2) The researcher who concerns more with the feelings and attitudes of the people involved in the organization studied: “feeling” researcher

1. “Resources” researchers

The first ones are more akin to the position of the natural scientist, and for them, the reality is represented by objects that are considered to be “real”, “touchable” and “visible”, such as computers, trucks and machines. Actually, “resources” researcher´s data are presented in the form of a table of statistical data. E.g. estimated personal computers users:

Estimated personal computers users
Country Computers
USA 223,810,000
Japan 69,200,000
China 52,990,000
Germany 45,000,000
Uk 35,890,000
France 35,000,000
South Korea 26,201,000
Canada 22,390,000
Italy 21,486,000
Brazil 19,350,000

Apart from resources, the existence of such sophisticate research methods as survey, allow researchers measure also opinions and attitudes. Imaging your research aims to measure the labor satisfaction in a manufacturing company. You may perform a survey and ask such questions as below:

“Are you very satisfied, somewhat satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, very dissatisfied within the company?

  1. Very satisfied
  2. Somewhat satisfied
  3. Neither satisfied nor dissatisfied
  4. Somewhat dissatisfied
  5. Very dissatisfied

As such, the results might be represented as below:

Level of satisfaction %
Very satisfied 40
Somewhat satisfied 35
Neither satisfied nor dissatisfied 20
Somewhat dissatisfied 4
Very dissatisfied 1

 

These “resources” researchers would argue that this kind of data is less open to bias and therefore more objective. They think that the object studied by the “feeling” researchers cannot be seen, measured and modified like computers, trucks and machines.

As well as nature scientist, “resources” researchers also aim that the end product can be law-like generalizations, similar to those produced by physical and natural scientist. In our example of workers satisfaction, another question of the survey questionnaire might be:

Which department do you belong to?

  1. Manufacturing department
  2. Marketing department
  3. Accounting department
  4. Logistic department

Obtaining as a result the below table and being able to make law-like generalization as: “Employed satisfaction is 20% higher among manufacturing department workers than in the rest of the department”

%

Manufacturing department Marketing department Accounting department Logistic department
Very satisfied 80 58 62 59
Somewhat satisfied 10 12 8 9
Neither satisfied nor dissatisfied 5 3 2 7
Somewhat dissatisfied 3 5 3 2
Very dissatisfied 2 2 5 1

2. “Feeling” researchers

But, does this data presented in statistical tables deserve more authority than those presented in a narrative by a “feeling” researcher? You may be critical of “resources” researchers view and argue that the social world of business and management is far too complex to be understood just by numbers.

“Feeling” researchers advocates that it is necessary for the researcher to understand differences between humans in our role as social actors. Before further explanations of what is a social actor, watch the below video.

This video, emphasize the importance of the context, i.e. how important is where we are to the way we behave. Many of the people passing by the famous violinist would have paid more than 100$ for attending one of his concerts, but in this precise context, not even stopped to listen to him.

At the same way, you as students might be making jokes and laughing if you were outside or in a party, but as you have been tough that in a class you are supposed to behave, you don’t make jokes. Because there is something called social norms: being in silence, raise your hands when I ask you for, say good afternoon when entering in classroom, just example of social norms that are not written anywhere but all of us know.

Following this social norms we become in social actors, and play different roles depending on the context.

What are the implications for your own research? Coming back to the example given previously about the satisfaction in a manufacturing company, you, as “resources” researcher might be content with the result and might not want to go further. However, as “feeling” researchers you might prefer to go further and try to study more closely the feelings of the workers, as well as their beliefs, values, concerns. For this reason you perform a number of in-depth interviews. After recording the interviews, listening carefully and analyzing the information, you will unlikely to represent it by statistic tables, but you will be able to perform a narrative as the one given below:

Most of the interviewed sustain that they are satisfied, but mainly thanks to the “good salaries” (Joe). But the truth is that many of them feel quite unsatisfied in terms of development, because the tasks they do are “quite boring” (Peter). On top of that, some of them think that they are satisfied with the job, but in a long term they would prefer to leave the company for doing something “more challenging” (Mary)”…

A “resources” researcher would think that this is not objective, because you analysis is affected by the context and the answer given by the worker may be biased. On top of that, the number of interviews is not enough and it is not representative of the total number of the workers.

The truth is that a “feeling” researcher do not highly focus on “representativity” and “objectivity” as “resources” researchers do, but they gain, by contrast, major deepness in their analysis and major ability to identify the smallest details of worker satisfaction.

If you are more “resources” researcher, you will likely embrace what is called the positivism, whereas if you are more “feeling” researcher, you will likely embrace interpretivism. (There are also another philosophical position called realism that will not be address here and which essence is that what the senses show us as reality is the truth. You can find more details here)

The metaphor of iceber illustrate very well the difference between both philosophies. In case of perfoming a research on a company culture, a positivist (“resources” researcher”) will aim to understant the visible part of the iceber, which corresponds with goal technology, structure, policies and proceedures, products/services and financial resources, among other, or what is called formal aspects of the organization. By contrast, a interpretativist (“feeling” researcher) will aim to undertand such questions as beliefs, attitudes and values, among others, or what is called “informal aspects of the organization.

Within this post it would be easy to fall into the trap of thinking that one research philosophy is “better” than another. This would miss the point. They are “better” at doing different things. When doing a research on labour satisfaction, adopting both philosophies is as possible as applying, provided that you own enough resources and skills, both a survey and in-dept interviews. For example, taking advantage of the information obtain by mean the in-depth interviews you will be able to formulate more focused questions and obtain more specific data. Coming back o our previous example, once you know that the satisfaction depends not only in salary but also in expectation and in oing interesting task, your survey questionaire could include apart from the general question on satisfaction, another kind of question as: “how satisfied are you in terms of personal development”, “…and in terms of salary…”

Finally, after reading this post you still think that choosing between one position and other is somewhat urealistic in practice, perhaps you should consider read this other post on pragmatism.

References

Camino, J. R. (2011). Cómo escribir y publicar una tesis doctoral ESIC Editorial.

Gene Weingarten (April 8, 2007). Pearls Before Breakfast. Washington Post. Retrieved from http://www.washingtonpost.com

Lewis, P., Saunders, M. N. K., & Thornhill, A. (2009). Research methods for business students Pearson.

Stanley N. Herman (1970) Cultural Iceber. TRW Systems Group. Retrieved from http://sandylearningblog.wordpress.com

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