Past Events

Tuesday 10 December 2019, University of Manchester, 11.00-14.00

This stream will focus on the challenges of using various kinds of qualitative interviewing as a primary method of data generation, whether in the form of unstructured and semi-structured interviewing, narrative methods, oral and life history interviewing, focus groups, creative interviewing methods or other elicitation techniques.

As well as considering the practical and ethical challenges of working with such methods, the stream will also focus on the analytical challenges of working with qualitative interview data. Topics of interest to expand upon include (but are in no way limited to) the following:

• researcher positionality and insider-outsider research;
• the use of creative and sensory methods in interview-based fieldwork;
• epistemological and practical challenges of working with interview data;
• combining interview data with other forms of data;
• different approaches to analysis;
• the use of qualitative data analysis software.

Academic lead for 2021/22: Dr Rose Pritchard : rose.pritchard@manchester.ac.uk

Dr Rose Pritchard is Research Fellow in Social-Environmental Systems in the Global Development Institute at the University of Manchester. A lot of my research focuses on the social implications of forest change, both in terms of deforestation and forest restoration. I’m also really interested in the increasing use of ‘big’ environmental data in forest restoration and other forms of conservation. My work is very much mixed methods, including both quantitative survey approaches and the kinds of qualitative interview methods which are the focus of this MNW stream

Manchester (Friends’ Meeting House) / 21 & 22 November 2019

Call for participation: Critical ethnographies of green transition

A growing technosphere, drastic biodiversity loss and increasing climate chaos contribute to dramatic socio-ecological changes across the planet. Droughts, floods, resource shortages, mega-infrastructure, shifting species distributions, soil degradation and other phenomena impact livelihoods and indeed survival opportunities.

Experienced and comprehended in many different ways, these changes provoke a variety of different responses. Whether top-down or bottom-up,  initiatives for transitions to sustainability are mushrooming. From ‘green economy’ strategies and high-tech fixes to grassroots initiatives and social movements, envisioned sustainability transitions and their material realisations take on various forms, at different scales, all over the world: offshore wind farms, biorefineries, carbon markets, geoengineering, tax cuts for electric cars, photovoltaic roof tiles, guerrilla gardening, ecosystem restoration camps, permaculture conventions, off-grid communities, indigenous uprisings, to name but a few. These different initiatives embody conflicting visions of a ‘green’ future and the pathways to get there and may have uneven effects.

This workshop will provide an opportunity to exchange research experiences and visions with regard to ethnographically studying “green transition initiatives” in a variety of fields (e.g. energy, transport, food production), at different scales (e.g. neighbourhood, watershed, intercontinental), and led by different actors (e.g. government,
industry, civil society). Our intention is to create the foundation for a network of support and exchange.

Keynotes-

Deepa Joshi (Gender, Youth and Inclusion Lead: International Water Management Institute);

Sarah Marie Hall (Senior Lecturer in Human Geography, ISRF Political Economy Research Fellow: University of Manchester);

Patrick Bigger (Lecturer, Critical Geographies Group, Lancaster Environment Centre: University of Lancaster)

A virtual Q&A session with Prof Gillian Hart (UC Berkeley)

–

Participation is free, but numbers are limited (maximum 20) – full call and short application form: https://criticalethnographies.wordpress.com/ – Please apply by 25 October 2019!

Non-academic practitioners, PhD students and early career researchers are particularly encouraged to apply, especially (but not exclusively) those from the North West Social Science Doctoral Training Partnership universities. Some financial support is available for participants without institutional funding.

28th October 2019 at The University of Manchester from 10.30am to 4.45pm.

Building on the success of the 2017 Methods Fair, which focused on creative ways of presenting research findings and engaging audiences, this year’s theme explores creativity in the methods researchers use and how creativity can enhance research practices, including data generation and recording, analysis and data presentation.

Creative research methods have developed and multiplied in recent decades, providing alternative ways of knowing and understanding the world, as well as answering complex research questions that cannot be achieved by traditional methods alone. However, researchers are also being creative with conventional research methods and approaches to analysis. We aim to showcase the various ways creativity drives all kinds of social science research and methodologies, from the conception of an idea, to creative ways of generating, collecting, recording, analysing and presenting data.

The methods@manchester Methods Fair 2019 is a free event, however, registration is required.

10 June 2019, 9am-5pm, Roscoe Building, The University of Manchester, UK, M13 9PL

Registration is now open for this joint conference organised by the Cathie Marsh Institute for Social Research and methods@manchester.

Conference outline

The conference is multi-disciplinary and focuses on methodological innovation in a wide range of fields including sociology, economics, criminology, health and geography. The methods showcased are diverse and range from new automated approaches to dealing with large scale ‘noisy’ forms of big data to more personalised strategies that centre on co-production and citizen involvement. A key theme of the conference is highlighting methodological innovation across the stages of the research process, i.e. from initial research design to data collection, the use of extant data sources, analysis, the presentation and dissemination of results, and engaging with the public.

Structure to the day

The morning will begin with a keynote presentation, ‘Reflections on Methodological innovation: Challenges and opportunities’ from Professor Jane Elliott, University of Exeter.

In the afternoon, Dr Tom Smith, Managing Director of the new ONS Data Science Campus will deliver his keynote, ‘New forms of data for official statistics’.

The afternoon will provide two optional activities for attendees, which will be confirmed once conference registration closes on 31 May 2019:

1. A data hackathon organised by the National Centre for Research Methods (NCRM). In the hack, those participating will be given a set of datasets and asked to perform an analysis which requires information from some of the datasets.  The datasets are imperfect and participants will have to manage those imperfections.
2. A screening of a documentary film of an arts-based project about the process of recovery from substance use introduced by Professor Amanda Ravetz, Manchester Metropolitan University.

Presentations throughout the day

Presentations will take place in concurrent sessions that will run across the whole day. Presenters and paper titles are listed below:

• Alastair Roy – A critical discussion of the use of film in participatory research projects with homeless young people: an international case-case based analysis
• Charlotte De Kock – Monitoring migration-related indicators in European drug treatment: Identifying pitfalls and challenges in registration, data collection and database coupling methods 
• Emma Heron – Listening Matters!: The Challenge of Genuine Listening in a Higher Education Setting for the Purpose of Change
• Hanako Smith – Experience Sampling Method in a Living Labs approach: How to connect with millennials in a real-world setting
• Jerome Turner – The Community Panel method: working collaboratively with participants in Facebook Groups.
• Josephine Biglin – ‘Participatory Epistemology and Non-representational Theory: Initial Experiences of Working with Migrant Populations
• Karina Williams – ONS social media analysis of YouTube data
• Kirsty Fife – Challenging Voices: Methods for Documenting and Archiving UK DIY Music Spaces
• Martin Greenwood – Reading the signals: Capturing the meanings of pedestrian crossings practice in Manchester using participant observation and dual-perspective GoPro ethnography
• Matthew Sanderson – Can existing, cross-sectoral community engagements better inform the development of power network design and planning?
• Michelle Van Impe – What do we want and where are we now? Critical methodological reflections on participatory action research with people who use illegal drugs
• Miriam Trzeciak – ‘Tell us something about yourself, too’ – Reflections on Collaborative Research as a Reflexive Tool for Social Research.
• Oana Petcu – What features impact engagement with missing people appeals on twitter?
• Peter Barbrook-Johnson – Participatory Systems Mapping for understanding complex societal issues
• Peter Smyth – Processing Large Datasets using Columnar Datastores on the Desktop
• Ratna Ghosh – A reflexive account of participatory video action research: The stories that middle-class women in urban India don’t want to share
• Rosalind Edwards – Big data, qualitative style: a breadth-and-depth method for working with large amounts of secondary qualitative data
• Sally Ruth Fergusson-Wormley – “Embedding the voice” – Co-producing a PhD

Registering for the event

This is a not-for-profit conference. We are making a small charge to attendees as a contribution to some of the costs.

17th May 2019, University of Liverpool

Overview

The Third Annual Methods X Conference is being held in the University of Liverpool on Friday the 17th May 2019. It represents an opportunity for postgraduate researchers from across the region to come together to showcase and discuss the methods and methodologies at the centre of their research and exchange ideas, experiences and insights. It is also an opportunity to enjoy Light Night in Liverpool, the city’s annual free one-night arts festival, with a large number of arts and cultural events taking place across the city from the late afternoon onwards.

Dr Faiza Shaheen

We are extremely pleased to announce that the morning programme will include a keynote by Dr Faiza Shaheen, Director of the Centre for Labour and Social Studies, and an economist by training, who undertook her PhD in the North West, discussing the importance of social research in the contemporary world, as well as talks by three post-doctoral researchers recently awarded their PhDs in the North West – Dr Cat Mahoney, Dr Kirsty Morrin and Dr Eileen Turnbull – on innovation and impact in and through research and how method helps underpin it.

The afternoon programme will involve paper sessions involving contributions from current PGRs organised around the four main North West methods exchanges – the Archives, Collections and Documents of Life Methods Exchange, the Fieldwork Methods Exchange, the New Forms of Data Methods Exchange and the Quantitative Methods Exchange.

Registration and Call for Papers

All PGRs in the NW are welcome to attend the conference and we invite attendees to submit paper proposals for the afternoon sessions. 

Wednesday 16 January, 12.00 – 3.00pm Room 2.07, Humanities Bridgeford Street, The University of Manchester

You are invited to the first seminar of the interdisciplinary seminar series: ‘Evaluation, Measurement and Assessment’ organised by The University of Manchester and Lancaster University. This initiative is funded by Methods North West with support from the ESRC and North West Social Science DTP. The aim of the seminars is to bring together researchers from various fields in Social Sciences to present and discuss issues around evaluation studies in different areas and advancements in the assessment of cognitive and social skills (e.g. performance, attitudes, dispositions, etc).

Speakers

Dr Gemma Derrick, Senior Lecturer in Higher Education, Lancaster University – Looking at the peer review processes as an evaluative practice in academia

Prof Julian Williams, Professor of Mathematics, Manchester Institute of Education, The University of Manchester – Why the ‘what works’ policy isn’t working and what we can do about it

The seminar is open to academics, researchers and PhD students.

Lunch will be provided between 12.00-1.00pm. For more information or questions please contact Sofia Eleftheriadou, sofia.eleftheriadou@manchester.ac.uk

The University of Manchester from 2 July to 13 July 2018

Each course at the school will run for one week, offering four days of content to a five-day timetable (Monday afternoon to Friday lunch-time), building on successful methods@manchester and CMIST short-courses given throughout the year.

The school offers a range of specialised courses covering a variety of topics that are particularly relevant to postgraduate and ECR research in humanities and social sciences. The selection includes software training, qualitative and quantitative analysis, area studies, and research design. The course content is based on approaches from across the various schools in the Faculty of Humanities at the University of Manchester.

Courses running in 2018:

• Generalized Linear Models: a comprehensive system of analysis and graphics using R and the Rcommander
• Getting Started in R: an introduction to data analysis and visualisation
• Structural Equation Modelling with MPlus
• Introduction to social network analysis using UCINET and Netdraw
• Statistical analysis of social networks
• Social Media Analysis
• Quantitative Longitudinal Data Analysis

Each course will deliver four days of content to a five-day timetable unless otherwise stated (Monday afternoon to Friday lunch-time).  Places are limited, so please book early to secure your place. The course fee is for a single course and includes 28 hours of face-to-face teaching over five days, and lunch on four days.

Bursaries

We have a small number of bursaries available for University of Manchester PhD Students (reducing the cost of a week-long course to £300) and UK wide PhD Students (reducing the cost of a week-long course to £400).

If you would like to apply for a bursary, please email methods@manchester.ac.uk for an application form.

A free event for local authorities, public health teams, police, event organizers, promoters, media, clubbers, drug users and interested others.

Under global prohibition, users of illegal drugs cannot be assured of the content of the drugs they take.  Services that provide forensic testing of substances submitted by users are leading the way in allowing drug users to make more informed choices.  But what are the legal, moral and practical challenges of providing this kind of service?  We find out from three leading European testing services.

Confirmed speakers:

• Monica Barratt (Drug Policy Modelling Program, UNSW, Australia)
• Mireia Ventura (Energy Control testing service, Spain)
• Tibor Brunt (DIMS testing service, the Netherlands)
• Fiona Measham (Co-founder of The Loop, UK)
• Henry Fisher (Policy Director, VolteFace POlicy Innovation Hub)
• Oliver Sutcliffe (Manchester Metropolitan University)

26-30 June and 3-7 July 2017, University of Manchester

Creative Approaches to Qualitative Researching course forms a part of the methods@manchester Summer School 2017.  The Summer School features a number of qualitative researching, quantitative research and software courses.

Course content overview

This intermediate level course offers a hands-on introduction to creative approaches to doing qualitative research. The various stages of research will be covered, from data collection and analysis through to writing with qualitative data. We begin by introducing what we mean by doing qualitative research creatively, before moving on to consider ‘Facet methodology’, an inventive orientation to researching the multidimensionality of everyday lives, which puts the researcher’s creativity and imagination at the heart of methodological practice. The course also explores some of the practical and ethical issues in using creative methods. Participants will be given a practical and hands-on introduction to a range of creative qualitative methods, including visual methods and ‘material methods’. The course will also cover key principles in qualitative data analysis, and how these can be put into practice. Finally, we discuss practical and intellectual strategies for writing with qualitative data, and consider how it is possible to theorise, or write conceptually, with such data. The course includes several practical workshop exercises involving creating and analysing qualitative data, where participants will have the opportunity to work with their own data.

Course objectives:

This course will

• Introduce students to creative methods both as an approach, and as a means of generating social science research data
• Introduce students to a range of creative methods
• Give students practical experience in the use of creative methods
• Introduce students to analytical strategies appropriate to creative methods
• Introduce students to strategies for writing with qualitative data

26-30 June and 3-7 July 2017, University of Manchester.

The Getting Started in R – an introduction to data analysis and visualisation course forms a part of the methods@manchester Summer School 20177.  The Summer School features a number of qualitative researching, quantitative research and software courses.

Course content overview

R is an open source programming language and software environment for performing statistical calculations and creating data visualisations. It is rapidly becoming the tool of choice for data analysts with a growing number of employers seeking candidates with R programming skills.

This course will provide you with all the tools you need to get started with data analysis and visualisation with R. We will introduce the tidyverse, a collection of R packages created by Hadley Wickham and others which provides an intuitive framework for using R for data analysis. Students will learn the basics of R programming and how to use R for effective data analysis. Practical examples of data analysis on social science topics will be provided.

Course outline
1. R and the ‘tidyverse’
This session will introduce R & RStudio and cover the basics of R programming and good coding practice. We will also discuss R packages and how to use them, with a particular focus on those that make up the ‘tidyverse’. We also introduce R Markdown which will be used to report our analyses throughout the course.
2. Import and Tidy
Data scientists spend about 60% of their time cleaning and organizing data (CrowdFlower Data Science Report 2016: 6). This session will show you how to ‘tidy’ your data ready for analysis in R. In particular, we’ll show you how to take data stored in a flat file, database, or web API, and load it into a dataframe in R. We will also talk about consistent data structures, and how to achieve them.
3. Transform
Together with importing and tidying, transforming data is one of the key element of data analysis. We will cover subsetting your data (to narrow your focus), creating new variables from existing ones, and calculating summary statistics.
4. Visualise
Data visualisation is what brings your data to life. This session will provide you with the skills and tools to create the perfect (static and interactive) visualisation for your data.
5. Bringing it all together
In this last session we review all we have learned on this course, and think about how we can bring it all together in dynamic outputs, such as interactive documents, plots, and Shiny applications.

Course objectives:

After this course, users should be able to:

• implement the basic operations of R;
• read data in multiple forms;
• clean, manipulate, explor and visualise data in R

26-30 June and 3-7 July 2017, University of Manchester.

The Structural Equation Modelling with MPlus course forms a part of the methods@manchester Summer School 2017. The Summer School features a number of qualitative researching, quantitative research and software courses.

Course content overview

This course gives a hands on introduction to what is possible in a latent variable analysis framework using Mplus. Building up the different sides of latent variable modelling and structural equation modeling step by step, eight different types of analysis are tackled.

Regression, Path Analysis, Confirmatory Factor Analysis, Item Response Theory, Measurement modelling, Latent Class Analysis, Longitudinal Analysis and lastly, hybrids of these are all topics of the course covered in lectures and practical analysis in Mplus.

Bringing your own data and research questions is highly recommended!

Course objectives:

1. Distinguish and understand different types of latent variable analysis;
2. Learn how to do basic and advanced structural equation modelling;
3. Understand how to combine different techniques in one model; and
4. Learn how to use Mplus

Course timetable

Day one
Afternoon – Regression

Day two
Morning – Path Analysis
Afternoon – Confirmatory Factor Analysis

Day three
Morning – Item Repsonse Theory
Afternoon – Measurement Modelling.

Day four
Morning – Latent Class Analysis
Afternoon – Longitudinal Modelling

Day five
Morning – Model Building

26-30 June and 3-7 July, University of Manchester

The Generalized Linear Models: a comprehensive system of analysis and graphics using R and the Rcommander course forms a part of the methods@manchester Summer School 2017.  The Summer School features a number of qualitative researching, quantitative research and software courses.

Course content overview

This is a general course in data analysis using generalized linear models.  It is designed to provide a relatively complete course in data analysis for post-graduate students.  Analyses for many different types data are included; OLS, logistic, Poisson, proportional-odds and multinomial logit models, enabling a wide range of data to be modelled.  Graphical displays are extensively used, making the task of interpretation much simpler.

A general approach is used which deals with data (coding and manipulation), the formulation of research hypotheses, the analysis process and the interpretation of results.  Participants will also learn about the use of contrast coding for categorical variables, interpreting and visualising interactions, regression diagnostics and data transformation and issues related to multicollinearity and variable selection.

The software package R is used in conjunction with the R-commander and the R-studio.  These packages provide a simple yet powerful system for data analysis.  No previous experience of using R is required for this course, nor is any previous experience of coding or using other statistical packages.

This course provides a number of practical sessions where participants are encouraged to analyse a variety of data and produce their own analyses.  Analyses may be conducted on the networked computers provided, or participants may use their own computers; the initial sessions cover setting up the software on lap-tops (all operating systems are allowed).

Course objectives:

The main objective of this course is to provide a general method for modelling a wide range of data using regression-based techniques.  Participant will be able to select, run and interpret models for continuous, ordered and unordered data using modern graphical techniques.

26-30 June and 3-7 July 2017, University of Manchester

The Introduction to social network analysis using UCINET and Netdraw course forms a part of the methods@manchester Summer School 2017.  The Summer School features a number of qualitative researching, quantitative research and software courses.

Course content overview

This is an introductory course, covering the concepts, methods and data analysis techniques of social network analysis. The course is based on the book “Analyzing Social Networks” by Borgatti et al. (Sage) and all participants will be issued with a copy of the book. The course begins with a general introduction to the distinct goals and perspectives of social network analysis, followed by a practical discussion of network data, covering issues of collection, validity, visualization, and mathematical/computer representation. We then take up the methods of detection and description of structural properties, such as centrality, cohesion, subgroups and positional analysis techniques. This is a hands on course largely based around the use of UCINET software, and will give participants experience of analyzing real social network data using the techniques covered in the workshop. No prior knowledge of social network analysis is assumed for this course.

Course objectives:

This course will

• Introduce the idea of Social Network Analysis
• Explain how to describe and visualise networks using specialist software (UCINET)
• Explain key concepts of Social Network Analysis (e.g. Cohesion, Brokerage).
• Provide hands-on training to use software to investigate social network structure

Course timetable

Day one
Introduction to Social Network Analysis, terminology and the software UCINET/Netdraw.  Chapters 1 and 2

Day two
Morning – Collecting social network data and research design. Chapters 3 and 4
Afternoon – Data management and visualisation. Chapters 5 and 7

Day three
Morning – Multivariate techniques and whole networks. Chapters 6 and 9.
Afternoon – Centrality and ego networks. Chapters 10 and 15.

Day four
Morning – Equivalence and core-periphery. Chapter 12
Afternoon – Subgroups and two-mode networks. Chapters 11 and 13

Day five
Morning – Testing hypothesis and large networks. Chapters 8 and 14.
Chapter numbers refer to the book “Analyzing Social Networks) by Borgatti et al. (Sage).  Timetable is subject to change.

26-30 June and 3-7 July 2017, University of Manchester

The statistical Analysis of Social Networks course forms a part of the methods@manchester Summer School 2017.  The Summer School features a number of qualitative researching, quantitative research and software courses.

Course content overview

This is an introduction to statistical analysis of networks. While no strict prerequisites are assumed, you might find it helpful to have some basic knowledge of social network analysis beforehand. To benefit fully from the course requires a basic knowledge of standard statistical methods, such regression analysis. The course aims to give a basic understanding of and working handle on drawing inference for structure and attributes, both cross-sectionally as well as longitudinally. A fundamental notion of the course will be how the structure of observed graphs relate to various forms of random graphs. This will be developed in the context of non-parametric approaches and elaborated to analysis of networks using exponential random graph models (ERGM) and stochastic actor-oriented models. The main focus will be on explaining structure but an outlook to explaining individual-level outcomes will be provided.