Undergraduate study - 2021 entry

Degree Programme Specification 2020/2021

Social Policy with Quantitative Methods

To give you an idea of what to expect from this programme, we publish the latest available information. This information is created when new programmes are established and is only updated periodically as programmes are formally reviewed. It is therefore only accurate on the date of last revision.
Awarding institution: The University of Edinburgh
Teaching institution: The University of Edinburgh
Programme accredited by: N/A
Final award: MA Honours
Programme title: Social Policy with Quantitative Methods
UCAS code: 4T6H
Relevant QAA subject benchmarking group(s): Social Policy
Postholder with overall responsibility for QA: Dr Alison Koslowski
Date of production/revision:

September 2016

External summary

Social Policy is concerned with the ways in which public policies, market forces and social institutions affect well-being in contemporary societies. Many of the programmes of modern states are directed at social policy outcomes. Social policies can be seen as efforts by societies to respond to the pressures of social, economic and technological change. Social Policy appeals to students who are interested in current political and social issues – such as how to organise and pay for health care, reduce inequalities, or accommodate a more diverse and individualised society. In Edinburgh, these issues are explored in a Scottish, a UK-wide, a European, and an international context. It is genuinely multi- disciplinary and draws on a variety of perspectives, e.g. sociological, political, economic, historical and legal perspectives. This degree has been developed as a strategic response to employers’ request to have more quantitatively trained graduate social scientists. Students with quantitative skills integrated with an understanding of social policy are very attractive to a range of employers, as they will be able to effectively engage with and produce social statistics.

Educational aims of programme

The programme aims to develop:

 

  • A sound and working knowledge of the use of statistics in social science at an advanced level;
  • A sound knowledge of the major fields of study within social policy;
  • Substantive knowledge of a range of areas of social policy analysis and the empirical evidence underlying them, informed by an active research culture;
  • The ability to understand, evaluate and use a range of theoretical frameworks from contemporary social policy;
  • The ability to use both quantitative and qualitative methods to collect, evaluate and interpret empirical evidence, and undertake independent research;
  • The capacity to apply social policy knowledge to the understanding and evaluation of social issues and problems in the contemporary world;
  • Key generic skills in critical thinking, evaluation of evidence, conceptual analysis, logical argument and oral and written communication;
  • To equip students for progression to a wide variety of careers or to further academic study.

Programme outcomes: Knowledge and understanding

On completion of the programme students should be able to:

  • Demonstrate knowledge and understanding of key concepts and theoretical approaches within Social Policy;
  • Demonstrate knowledge and understanding of the use of maths in social science;
  • Demonstrate a working knowledge of advanced statistics for social science;
  • Understand the relationship between social policy argument and empirical evidence;
  • Use of a range of research strategies and methods to gain social policy knowledge.

How is this accomplished?

  • Compulsory and optional elements in the curriculum ensure coverage of the points above;
  • Course handbooks, lectures, lecture handouts, tutorials, statistical lab sessions, seminars, and presentations, delivered face to face, via hard copy or electronically, are the key channels for dissemination of knowledge and guidance to further reading and research;
  • Content and assessment of courses and the requirements of the compulsory project/dissertation ensure cumulative knowledge and critical engagement with key concepts, theoretical approaches and research strategies within Social Policy, with a particular emphasis on quantitative methods;
  • Essays, examinations, oral presentations, statistical lab sessions and project work require independent reading and research beyond knowledge and understanding provided in the classroom;
  • Essays, examinations, oral presentations, contributions to statistical lab sessions and project work encourage application of alternative and comparative perspectives on and explanations of social phenomena, the weighing of evidence and argument and the identification of what is distinctive about social explanation;
  • Diversifying assessment allows students to perfect a broad range of academic skills.

Programme outcomes: Graduate attributes - Skills and abilities in research and enquiry

Graduates in Social Policy with Quantitative Methods will be able to create new knowledge and opportunities for learning through the process of research and enquiry, including the abilities to:

 

  • Undertake advanced quantitative analysis of data;

  • Apply different theories to the interpretation and explanation of social processes or structures;

  • Recognise and account for the use of such theories by others;

  • Evaluate, critique, and build on the work of social policy scholars;

  • Evaluate and critique policy documents from policy-making bodies;

  • Discuss and assess empirical evidence and theoretical argument in a clear and reasoned way;

  • Understand the ethical implications of social enquiry;

  • Select and use appropriate methods of social enquiry, to identify a range of different research; strategies and methods and to comment on their relative advantages and disadvantages

  • Judge the value and relevance of empirical evidence and theoretical argument and interpretation in social study;

  • Plan and carry out a research project and report its findings appropriately;

  • Creatively and constructively identify and design ways of solving problems with a social dimension;

  • Recognise, build on, and transcend the boundaries of the various social science disciplines – their empirical methods and their analytical traditions - in the pursuit of publicly useful knowledge.

 

Programme outcomes: Graduate attributes - Skills and abilities in personal and intellectual autonomy

Graduates in Social Policy with Quantitative Methods will be able to work independently and sustainably, in a way that is informed by openness, curiosity, and a desire to meet new challenges, including the abilities and dispositions to:

  • Be independent learners who take responsibility for their own learning and are committed to continuous reflection, self-evaluation and self-improvement;
  • Be able to sustain intellectual interest by remaining receptive to both new and old ideas, methods, and ways of thinking;
  • Be able to make decisions on the basis of rigorous and independent thought, taking into account ethical and professional issues;
  • Be able to use collaboration and debate effectively to test, modify and strengthen their own views;
  • Be able to respond effectively to unfamiliar problems in unfamiliar contexts;
  • Have a personal vision and goals and be able to work towards these in a sustainable way.

In addition to the above these will be accomplished through:

 

  • Requirements for tutorials and statistical lab sessions to focus on students’ own reading, practical statistical work and reflection;
  • Requirements for completing written and oral coursework assignments independently;
  • Requirements for planning carrying out and writing up the research project within a given timetable;
  • Requirement for self-directed study guided by course reading lists;
  • Requirements to for students to manage their time effectively to meet deadlines.

 

Programme outcomes: Graduate attributes - Skills and abilities in communication

Graduates of the School of Social and Political Science will recognize and value communication as the tool for negotiating and creating new understanding, collaborating with others, and furthering their own learning, including the abilities to:

  • Make effective use of oral, written and visual means to critique, negotiate, create and communicate understanding;
  • Use communication as a tool for collaborating and relating to others;
  • Further their own learning through effective use of the full range of communication approaches;
  • Seek and value open feedback to inform genuine self-awareness;
  • Recognise the benefits of communicating with those beyond their immediate environments;
  • Use effective communication to articulate their skills as identified through self-reflection.

In addition to the above these will be accomplished through:

 

  • Requirements for and feedback on effective individual and group oral presentation and communication in tutorials, statistical lab sessions and seminars;
  • Assessed tutorial participation in some tutorials;
  • The requirements to communicate and present quantitative evidence effectively in core courses;
  • The requirement to design, carry out and report on a research project, and feedback on it;
  • The work placement.

Programme outcomes: Graduate attributes - Skills and abilities in personal effectiveness

Graduates in Social Policy with Quantitative Methods will be able to effect change and be responsive to the situations and environments in which they operate, including the abilities to:

  • Make constructive use of social analysis skills in personal, professional, and community life;
  • Apply understanding of social risks, in relation to diverse stakeholders, while initiating and managing change;
  • Be both adaptive and proactively responsive to changing social contexts;
  • Have the confidence to make decisions based on their understandings and their personal and intellectual autonomy;
  • Transfer their knowledge, learning, skills and abilities from one context to another;
  • Understand and act on social, cultural, global and environmental responsibilities, and help others to do the same;
  • Be able to work effectively with others, capitalising on their different thinking, experience and skills;
  • Be able to make effective use of quantitative evidence in contexts where evidence of diverse kinds is being debated;
  • Understand and promote effectively the values of diversity and equity, while also recognizing possible trade-offs between these.

 

How is this to be accomplished?

By the combination of skills acquired listed in the above section

 

Programme outcomes: Technical/practical skills

  • Library
  • IT skills
  • Research skills
  • Use of Statistical Package for the Social Sciences (SPSS) and other data processing software and word processing packages
  • Presentation skills and using presentation software
  • Awareness of data, its sources and uses

Programme structure and features

Social Policy with Quantitative Methods – Degree Programme Table

 

Semester 1

Semester 2

Year 1

Social Policy & Society

Politics of the Welfare State

 

Mathematics for Social Science

Introduction to Statistics for Social Science

 

40 credits outside subjects

Year 2

 

European Social Policy

Social Policy Enquiry

 

20 credits outside

Doing Social Research with Statistics

 

40 credits outside subjects

Year 3

 

DDSR

Analytical Perspectives in Social Policy

 

Statistical Modelling

Advanced QM Option

 

40 credits Social Policy options level 10

Year 4

 

Advanced QM Option

Advanced QM Option or Social Policy level 10

 

40 credits Social Policy options level 10

 

Dissertation 40 credits or Placement-based Dissertation

Notes: 60 – 80 credits for ‘with’ degree.

New QM courses

Year 1 & 2, Semester 1, Mathematics for Social Science

Learning objectives:

  • Social science problem solving with formal mathematic thinking
  • To cover the following topics
    • Gradients, equations and graphs of straight lines
    • Linear Regression
    • Graphs of quadratic functions, the solution of quadratic equations by computing the square and by the formula
    • Exponential and Logarithmic functions
    • Radian measure and trigonometric functions
    • Differentiation
    • Curve Sketching
    • Integration
    • Differential equations
    • Calculus of more than one variable
    • Vectors
    • Matrices
    • Eigenvalues and eigenvectors
    • Principal components

 

Year 1 & 2, Semester 2, Introduction to Statistics for Social Scientists

Learning objectives:

  • Social science problem solving with formal mathematic thinking
  • To cover the following topics
    • Gradients, equations and graphs of straight lines
    • Linear Regression
    • Graphs of quadratic functions, the solution of quadratic equations by computing the square and by the formula
    • Exponential and Logarithmic functions
    • Radian measure and trigonometric functions
    • Differentiation
    • Curve Sketching
    • Integration
    • Differential equations
    • Calculus of more than one variable
    • Vectors
    • Matrices
    • Eigenvalues and eigenvectors
    • Principal components

 

Year 1 & 2, Semester 2, Introduction to Statistics for Social Scientists

Learning objectives:

  • Basic SPSS skills, including graphical skills
  • Introduction to secondary data access and management
  • Understanding of measures of association
  • Appreciation of the difference between association and causality
  • An understanding of inference and the logic of sampling
  • Communicating basic statistics
  • The concept of control
  • Being able to construct 3 way cross-tabulations
  • An introduction to regression analysis

 

Year 2, Semester 2, Doing Social Research with Statistics

Pre-requisite: Introduction to Social Statistics for Social Scientists or conversion course

Learning objectives:

  • Data reduction techniques
  • Digital social research
  • Logistic regression
  • Using alternative software to SPSS
  • Ethics of survey fieldwork

 

Year 3, Semester 1, Statistical Modelling

Pre-requisite: Doing Social Research with Statistics

Learning objectives:

  • Multinomial and ordinal regression
  • Count data
  • Event history techniques
  • Log linear modelling
 

Honours options, semester long options (20 credits)

Pre-requisite: Statistical Modelling

Could include: SEM, Multilevel modelling, complex survey, panel data, cross-national models, latent variable techniques etc. Could also include courses shared with Mathematics (with separate tutorials and assessment). The options to be offered will be those which are being used in research in the School.

Indicative Honours Options 2016-2014 (not all options are available in any given year)

 

Please note that all these courses are available to Social Policy students but are NOT all run by Social Policy

 

SCPL10024

SV1

Analytical Perspectives in Social Policy

Semester 2

20

SCPL10010

SV1

Children's Rights

Semester 2

20

SCPL10002

 

Criminal Justice: Policy and Practice

Not delivered this year

20

SCPL10012

SV1

Dissertation (MA Social Policy)

Full Year

40

SCPL10005

SV1

Educational Politics and Policy

Semester 2

20

SCPL10007

 

Employment Policies

Not delivered this year

20

SCPL10027

 

Europeanising Education

Not delivered this year

20

IPHP10002

SV1

Global Politics of Public Health

Semester 2

20

SCPL10025

 

Globalisation and public health

Not delivered this year

10

SCPL10023

 

Governing The Social

Not delivered this year

20

SCPL10026

 

Health Policy Analysis

Not delivered this year

10

SCPL10008

 

Health Policy and Planning

Not delivered this year

20

IPHP10003

 

Health Systems Reform and Public Private Partnerships

Not delivered this year

20

SCPL10030

SV1

Health Systems: Strengthening and Reform

Semester 2

20

SCPL10021

 

International Criminal Justice Policy and Politics

Not delivered this year

20

IPHP10004

SV1

International Public Health Policy Project

Full Year

40

SCPL10015

 

Issues in Comparative Housing Policy

Not delivered this year

20

SCPL10028

 

Labour Market Policy in Europe

Not delivered this year

20

SCPL10009

 

Law and Social Policy

Not delivered this year

20

SCPL10017

 

Political Economy of the Welfare State

Not delivered this year

20

SCPL10029

SV1

Population Health and Health Policy

Semester 1

20

SCPL10016

 

Rethinking Families and Family Policies in Europe

Not delivered this year

20

IPHP10001

SV1

Social Determinants of Health and Public Policy

Semester 2

20

SCPL10020

SV1

Social Inequality and the Life Course

Semester 2

20

SCPL10022

SS1

Social Policy Year Abroad Assessment

Full Year

40

SCPL10003

 

Social Security

Not delivered this year

20

SCPL10004

 

The Social Division of Welfare

Not delivered this year

20

SCPL10013

 

Welfare, Justice and the State

Not delivered this year

20

SCIL10062

SV1

Designing and Doing Social Research

Semester 1

20

SCIL10063

SV1

Doing Survey Research

Semester 2

20

PLIT10067

SV1

The Politics of British Public Services

Semester 1

20

Progression:

Y1

Students must pass all subjects.

Y2

A pass in six courses overall, with a mark of 50% or more in required courses.

Y3

End of semester degree examinations

 

Students with sufficient credits may exit at end of Year 3 with BA Humanities and Social Science. Students who choose not to continue after year 3 of the Honours programme may also, with the discretion of the examination board, be awarded the BA.

Y4

Degree classification based on performance in 240 credits courses taken in Y3 and Y4, assessed in the year they are taken.

Teaching and learning methods and strategies

Study in most courses in years 1 and 2 combines lectures and small group tutorials. Most courses in years 3 and 4 combine lectures with student discussion and presentation. Courses in statistical methodology will include practical exercises and assessments in computer labs. The Dissertation is based on a work placement completed between the junior and senior honours years, and is conducted by the student on an individual basis guided by a series of supervision meetings with a member of staff.

Teaching and learning workload

You will learn through a mixture of scheduled teaching and independent study. Some programmes also offer work placements.

At Edinburgh we use a range of teaching and learning methods including lectures, tutorials, practical laboratory sessions, technical workshops and studio critiques.

The typical workload for a student on this programme is outlined in the table below, however the actual time you spend on each type of activity will depend on what courses you choose to study.

The typical workload for a student on this programme for each year of study
Start yearTime in scheduled teaching (%)Time in independant study (%)Time on placement (%)
Year 118820
Year 220800
Year 312880
Year 410900

Assessment methods and strategies

 

Assessment method balance

You will be assessed through a variety of methods. These might include written or practical exams or coursework such as essays, projects, group work or presentations.

The typical assessment methods for a student on this programme are outlined below, however the balance between written exams, practical exams and coursework will vary depending on what courses you choose to study.

The typical assessment methods for a student on this programme for each year of study
Start yearAssessment by written exams (%)Assessment by practical exams (%)Assessment by coursework (%)
Year 117578
Year 227865
Year 30892
Year 400100

Career opportunities

 

Other items

  • The subject area, together with on course students, external examiners and quality assurance procedures, continually monitors the quality of the organisation, content, and delivery of its teaching with the aim of achieving the highest standards.
  • The teaching of the first cohort of students will be the subject of a report to the Nuffield Foundation as a condition of their funding.  This will provide further external input on the quality of the programme.
  • Opportunities for overseas exchanges in year 3 are possible as long as the student can confirm that they will have the possibility to follow advanced QM options.