SC208-5-FY-CO:
Stratification Across the Life Course: Inequalities From Cradle to Grave

The details
2019/20
Sociology
Colchester Campus
Full Year
Undergraduate: Level 5
Current
Thursday 03 October 2019
Friday 26 June 2020
30
16 May 2019

 

Requisites for this module
SC101
(none)
(none)
SC203

 

SC203, SC277, SC385, SC830, SC831

Key module for

BA M900 Criminology,
BA M901 Criminology (Including Year Abroad),
BA M903 Criminology (Including Foundation Year),
BA M904 Criminology (Including Placement Year),
BA L3C8 Criminology with Social Psychology,
BA L3H8 Criminology with Social Psychology (Including Placement Year),
BA LHC8 Criminology with Social Psychology (Including Year Abroad),
BA LP33 Communications and Digital Culture,
BA LP34 Communications and Digital Culture (Including Placement Year),
BA P300 Communications and Digital Culture (Including Foundation Year),
BA PL33 Communications and Digital Culture (Including Year Abroad),
BA CL83 Sociology with Social Psychology,
BA CL93 Sociology with Social Psychology (Including Placement Year),
BA CLV3 Sociology with Social Psychology (Including Year Abroad),
BA L300 Sociology,
BA L301 Sociology (Including Year Abroad),
BA L304 Sociology (Including Foundation Year),
BA L306 Sociology (Including Placement Year),
BA LM38 Sociology and Criminology (Including Placement Year),
BA LM39 Sociology and Criminology,
BA LMH9 Sociology and Criminology (Including Year Abroad),
BA LMHX Sociology and Criminology (Including Foundation Year),
BA L3J9 Sociology with Human Rights (Including Placement Year),
BA L3M9 Sociology with Human Rights,
BA LMJ9 Sociology with Human Rights (Including Year Abroad),
BSC L315 Sociology (Applied Quantitative Research),
BSC L316 Sociology (Applied Quantitative Research) (Including Year Abroad),
BSC L317 Sociology (Applied Quantitative Research) (Including Placement Year),
BSC L310 Sociology with Data Science,
BSC L311 Sociology with Data Science (including Year Abroad),
BSC L312 Sociology with Data Science (including Placement Year),
BSC L313 Sociology with Data Science (including foundation Year)

Module description

This full year module shares the Autumn term lectures and classes with Researching Social Life II (SC203). In this part of the module, students are introduced to quantitative data analysis. The second term builds on the knowledge gained in the first and introduces students to the study of stratification across the life course, with an emphasis on the critical examination of empirical evidence on inequality in both Britain and the USA.

In the autumn this module introduces you to the principles and practice of quantitative data analysis. Students are first introduced to basic descriptive statistics and the fundamental concepts of statistical inference, then to measures of association for both continuous and categorical variables. The term ends with a focus on regression analysis, which is the most commonly used statistical model in social science. Students will learn how to conduct statistical analysis using IBM SPSS software in weekly lab sessions.

In the spring term, building on the knowledge gained in the previous term, students are exposed to a selective introduction to the study of stratification across the life course, with an emphasis on the examination of empirical evidence from Britain and the USA. Social stratification is the unequal distribution of scarce resources, and of the processes by which these resources are allocated to individuals, groups, and social positions.

The study of stratification is broad and occupies a central role in sociological research, encompassing studies of income and wealth inequality, occupational and class hierarchies, inequality of educational opportunity, poverty, social mobility between and within generations, gender and race-ethnic inequality, and the consequences of inequality. We will also pay particular attention to the life course perspective on stratification; in other words, how experiences in early life influence later events and choices in education, marriage, or health.

In this course, we examine specific examples of sociological research in selected areas, covering the concepts, theories, facts, and methods of analysis used by sociologists to understand different aspects of social stratification. The examples are not meant to provide a comprehensive overview, but rather to illustrate prominent questions in the field and how sociologists go about answering them.

Module aims

The aims of the module are to provide:

Substantive understanding of current key debates and recent empirical work in the field of social stratification

Improved ability to critically read scientific journal articles and to interpret quantitative evidence

Experience in formulating research questions and testable hypotheses, and applying these to real data

Module learning outcomes

In the process of taking this module, you will develop skills that are transferable to your undergraduate project, the labour market, or postgraduate work, when you complete your undergraduate studies. You will also appreciate more how sociologists go about applying their skills and knowledge to the empirical investigation of issues they study. Chiefly, upon successful completion of the module, you will:

Autumn term:

1. Have gained an understanding of the principles and practice of quantitative analysis in sociology
2. Have gained an understanding of the fundamentals of statistical inference
3. Have basic skills in analysing and presenting quantitative data using computer software IBM SPSS and Excel

Spring term:

4. Gain a substantive understanding of current key debates and recent empirical work in the field of social stratification
5. Have an improved ability to critically read scientific journal articles and to interpret quantitative evidence
6. Gain the ability to critically examine the link between theoretical framework, research questions, data choice, and modelling strategy
7. Be able to formulating research questions and testable hypotheses, and applying these to real data

Module information

After the introductory week, this course is divided into four two-week sections, each devoted to a stage in the life course. Every section contains two lectures (one each week), followed by a class discussion after the first lecture and a lab session after the second. The class discussion will include in-depth discussion of the readings, with particular attention paid to identifying the research question and discussing the analytical choices and evidence provided by the authors. The class takes most of its examples from the contemporary United Kingdom and the United States. In each lab session, we will formulate our own research questions and hypotheses based on our readings and discussions. Building on knowledge and skills gained in the autumn term, students will then use SPSS software to test these using data from the largest longitudinal study of UK households: Understanding Society (UKHLS).

Learning and teaching methods

Autumn term: 1 hour lecture in weeks 2-11 1 hour class in weeks 5 and 8 2 hour lab in weeks 2-4, 6-7 and 9-11 Spring term: 1 hour lecture in weeks 16-20, 22-25 2 hour lab in weeks 16-20, 22-25

Bibliography

  • MacInnes, John. (2017) An introduction to secondary data analysis with IBM SPSS statistics, London: Sage Publications Ltd.
  • Grusky, David B.; Weisshaar, Katherine R. (2014) Social stratification: class, race, and gender in sociological perspective, Boulder: Westview Press.
  • Field, Andy P. (2017) Discovering statistics using IBM SPSS., London: Sage Publications.
  • Field, Andy P. (2018) Discovering statistics using IBM SPSS statistics, London: SAGE.
  • Kathryn, Edin. (2014) 'Low income urban fathers and the “package deal” of family life', in Social stratification: class, race, and gender in sociological perspective, Boulder: Westview Press.
  • A House Divided - How Unaffordable Housing Drives UK Inequality | The Equality Trust, https://www.equalitytrust.org.uk/house-divided-how-unaffordable-housing-drives-uk-inequality
  • Field, Andy P. (©2018) Discovering statistics using IBM SPSS statistics, London: SAGE.
  • (2014) The P-value, Significance, and Friends Who Don't Believe You - YouTube.
  • (no date) The Correlation Coefficient Explained - YouTubeThe Correlation Coefficient Explained.
  • (no date) Population Mean And Sample Mean.
  • Zaidi, Batool; Morgan, S. Philip. (2017-08-30) 'The Second Demographic Transition: A Review and Appraisal', in Annual Review of Sociology. vol. 43 (1)
  • Vikki Boliver. (2011) 'Expansion, differentiation, and the persistence of social class inequalities in British higher education', in Higher Education: Springer. vol. 61 (3)
  • Geronimus, Arline T. (1996-2) 'Black/white differences in the relationship of maternal age to birthweight: A population-based test of the weathering hypothesis', in Social Science & Medicine. vol. 42 (4) , pp.589-597
  • Heckman, J. J. (2006-06-30) 'Skill Formation and the Economics of Investing in Disadvantaged Children', in Science. vol. 312 (5782) , pp.1900-1902
  • Lareau, Annette. (2011) Unequal childhoods: class, race, and family life, Berkeley: University of California Press.
  • Becker, Birgit. (2011-03) 'Social disparities in children's vocabulary in early childhood. Does pre-school education help to close the gap?', in The British Journal of Sociology. vol. 62 (1) , pp.69-88
  • Lynch, J.W.; Kaplan, G.A.; Salonen, J.T. (1997-3) 'Why do poor people behave poorly? Variation in adult health behaviours and psychosocial characteristics by stages of the socioeconomic lifecourse', in Social Science & Medicine. vol. 44 (6) , pp.809-819
  • (2010) Simple Explanation of Chi-Squared - YouTube.
  • Elder, Glen H. (1998-02) 'The Life Course as Developmental Theory', in Child Development. vol. 69 (1) , pp.1-12
  • Gibson, Jason; SRMO; Sage Research Methods. (2014) Sampling distributions, Texas, USA: Math Tutor DVD LLC.
  • Abendroth, Anja-Kristin; Huffman, Matt L.; Treas, Judith. (2014-10) 'The Parity Penalty in Life Course Perspective', in American Sociological Review. vol. 79 (5) , pp.993-1014
  • Hout, Michael. (2012-08-11) 'Social and Economic Returns to College Education in the United States', in Annual Review of Sociology. vol. 38 (1) , pp.379-400
  • Gibson, Jason; SRMO; Sage Research Methods. (2014) Central limit theorem: Part 1, Texas, USA: Math Tutor DVD LLC.
  • Treiman, Donald J. (c2009) Quantitative data analysis: doing social research to test ideas, San Francisco, CA: Jossey-Bass.
  • Gibson, Jason; SRMO; Sage Research Methods. (2013) The frequency distribution, Texas, USA: Math Tutor DVD LLC.
  • (no date) Population And Sample Standard Deviation.
  • Jackson, Michelle; Erikson, Robert; Goldthorpe, John H.; Yaish, Meir. (2007-09) 'Primary and Secondary Effects in Class Differentials in Educational Attainment', in Acta Sociologica. vol. 50 (3) , pp.211-229
  • Tomaskovic-Devey, Donald; Thomas, Melvin; Johnson, Kecia. (2005-07) 'Race and the Accumulation of Human Capital across the Career: A Theoretical Model and Fixed-Effects Application', in American Journal of Sociology. vol. 111 (1) , pp.58-89
  • Sullivan, Alice; Joshi, Heather; Leonard, Diana. (2010-03) 'Single-Sex Schooling and Academic Attainment at School and Through the Lifecourse', in American Educational Research Journal. vol. 47 (1) , pp.6-36
  • MACMILLAN, LINDSEY; TYLER, CLAIRE; VIGNOLES, ANNA. (2015-07) 'Who Gets the Top Jobs? The Role of Family Background and Networks in Recent Graduates’ Access to High-status Professions', in Journal of Social Policy. vol. 44 (03) , pp.487-515
  • Field, Andy P. (c2013) Discovering statistics using IBM SPSS statistics, London: SAGE.
  • (no date) Introduction to Statistics.
  • Steele, Claude. (2014) 'Stereotype threat and African American student achievement', in Social stratification: class, race, and gender in sociological perspective, Boulder: Westview Press.
  • Almazon, Elbert P.; SRMO; Sage Research Methods. (2017) An introduction to descriptive & inferential statistics, London, United Kingdom: SAGE Publications Ltd.
  • Gibson, Jason; SRMO; Sage Research Methods. (2013) Population and sample standard deviation, Texas, USA: Math Tutor DVD LLC.
  • Gibson, Jason; SRMO; Sage Research Methods. (2013) Population mean and sample mean, Texas, USA: Math Tutor DVD LLC.
  • Gibson, Jason; SRMO; Sage Research Methods. (2013) Populations and samples, Texas, USA: Math Tutor DVD LLC.
  • (2014) Independent t-test - Explained Simply - YouTube.

The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework Three Mini Homework Exercises 15%
Coursework Quantitative Data Analysis Report 17/01/2020 35%
Coursework Mini Essay 1 07/02/2020 10%
Coursework Mini Essay 2 21/02/2020 12%
Coursework Mini Essay 3 13/03/2020 13%
Coursework Mini Essay 4 24/04/2020 15%

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Nick Allum and Renee Luthra
Jane Harper, Student Administrator, Telephone: 01206 873052

 

Availability
Yes
Yes
Yes

External examiner

Dr Monika Krause
Resources
Available via Moodle
Of 175 hours, 23 (13.1%) hours available to students:
152 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information
Sociology

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