1 / 40

Making the Long View:

Making the Long View:. Archiving, Representing and Sharing a Qualitative Longitudinal Resource March 2005 – August 2006 www.lsbu.ac.uk/inventingadulthoods. Making the Long View. AIM

chin
Download Presentation

Making the Long View:

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Making the Long View: Archiving, Representing and Sharing a Qualitative Longitudinal Resource March 2005 – August 2006 www.lsbu.ac.uk/inventingadulthoods

  2. Making the Long View AIM Explore creative ways of overcoming ethical & practical problems involved in providing access to a qualitative longitudinal (QL) dataset

  3. CORE TEAM Sheila Henderson Janet Holland Sheena McGrellis Sue Sharpe London South Bank University Rachel Thomson Open University Making the Long View MLV TEAM Jorge Camacho Debby Holder London South Bank University

  4. Making the Long View: The dataset INVENTING ADULTHOODS • A unique QL study combining three ESRC-funded studies from 1996-2006 • Rich biographical accounts of all aspects of life of a diverse group of 100 young people (aged 11-17 in 1996) growing up at the turn of the 21st century

  5. Making the Long View: The dataset INVENTING ADULTHOODS Five areas England • Disadvantaged estate in the north • Isolated rural area • Affluent area in a southern commuter belt • Inner city area in the south Northern Ireland • Diverse communities of a city

  6. Making the Long View: The dataset INVENTING ADULTHOODS Methods • Biographical interviews (up to 6 rounds) • Focus groups • Lifelines • Memory books • Questionnaires • Research assignments

  7. Making the Long View Case Data • Individual interview audio cassette, MP3 file and transcript (up to 6) • Questionnaire (up to 3) • Focus group audio cassette and transcript (up to 2) • Lifeline (& follow-up) • Memorybook • Case profile (first level analysis post-interview: processual features, substantive content, and researcher’s reflections).

  8. Making the Long View THE WORK • Prepare a showcase ‘mini’ archive (10 cases) • Explore the potential for using the ‘mini’ archive • Establish a network of dataset users • Disseminate project findings

  9. Making the Long View ARCHIVING • Debates: our position • Motives • Contribution of the QL perspective • 3 dimensions of time: biographical, historical, research • Our continued contact with the YP • Ethical selection criteria • Consent: informed, participatory • Cleaning and anonymisation • The unforeseens

  10. Making the Long View CASE ARCHIVING PROCESS The 5 steps 1. Case selection 2. Consent 3. Data location, collation and digitisation 4. Cleaning 5. Anonymisation

  11. Making the Long View GLEN: THE BASICS • Sex: Male • Location: Northern Ireland • Interview age: 16-23 • Class: WC • Ethnicity: White Caucasian

  12. Making the Long View GLEN’S STORY • Parental split • Creative arts • Drugs and alcohol • Few resources • Homelessness • Violence • Reliance on intimate relationships

  13. Making the Long View GLEN’S DATA Interviews (transcript, audio tape, mp3 file) Date Age Interviewer 1: 2: 12/08/99 17 SMG 3: 23/11/00 19 SMG 4: 18/05/01 19 SMG 5: 17/01/03 21 SMG 6: 05/11/04 23 SMG

  14. Making the Long View GLEN’S DATA Other data Case profile Questionnaire: hard copy Focus group: transcript, audio tape Lifeline: hard copy

  15. Making the Long View Selection criteria • Diversity • Ability to cope • Data volume • Data quality • Contact-ability

  16. Making the Long View GLEN: Selection criteria • Different story / transitions • Policy interest • Data volume • Data quality

  17. Making the Long View GLEN: Selection criteria • Ability to cope ? • Contact-ability ?

  18. Making the Long View Consent • Initial verbal • Consent form (& information sheet) • Consult re anonymisation

  19. Making the Long View GLEN: Consent • Initial verbal • Consent form (& information sheet) • Contact and consultation: April September 2006

  20. Making the Long View Glen:Data collation & digitisation

  21. Making the Long View Cleaning

  22. Making the Long View Anonymisation: The QL context • Published analysis & interpretation • Pseudonyms and red herrings • A cumulative process: within case, within research site

  23. Anonymisation: The ‘snapshot’ study Making the Long View 1 2 3 4

  24. Anonymisation: The QL study Making the Long View 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

  25. Anonymising Glen Protecting against an internal audience Protecting yp from external audience Protecting against the cumulative effect over time within case Protecting against the cumulative effect over timecross- case within same site Making the Long View

  26. Protecting against an internal audience Possibilities: teachers, youth workers, youth advisers in benefit office; key workers in housing initiatives; other young people both in study and in his home town; journalist friend (so other journalists) Making the Long View

  27. Protecting yp from external audience Political significance of NI Less possibilities than other sites Change place and people names Red herrings Making the Long View

  28. Protecting against the cumulative effect within case Education and training Interest in music Making the Long View

  29. Protecting against the cumulative effect cross- case within same site Significance of a multi media centre Significance of places and people in the music scene Making the Long View

  30. Making the Long View THE LESSONS: ANONYMISING DATA • Anonymising QL data is a cumulative, labour intensive process • Listen to /read all interviews for a case before anonymising • Hold in the balance: internal and external ‘audiences’ for the dataset; cross-case and cross-research site considerations • Research sites vary in the degree to which they can be identified and need protection • Be prepared to return to transcripts from a particular research site as your knowledge and approach to anonymisation develops over time

  31. Making the Long View: Archiving, Representing and Sharing a Qualitative Longitudinal Resource March 2005 – August 2006 www.lsbu.ac.uk/inventingadulthoods

  32. Making the Long View CASE ARCHIVING COSTS

  33. Making the Long View COSTS First 10 cases: £17,625 - 00 Per case:£1,762 - 50

  34. Making the Long View: Archiving, Representing and Sharing a Qualitative Longitudinal Resource March 2005 – August 2006 www.lsbu.ac.uk/inventingadulthoods

  35. Making the Long View THE LESSONS: CONSENT & CONFIDENTIALITY • Take a positive approach. 100% confidentiality impossible but negotiate with respondents on this basis • Get the balance right: consultation / too much work; giving enough / too much information for consent • Investing intensive labour into a relationship that could fall apart: data preparation & consent process • A commitment to archiving data means distinguishing often unclear and confused questions: confidentiality & control and ownership of data

  36. Making the Long View THE LESSONS: MANAGING DATA • Think about how you store your data: by case, cross-sectionally or both? • Take a pragmatic approach to making technological decisions (e.g. digital audio file type), balancing quality and future-proofing with budget and storage space • Clean and negotiate archiving consent as you go but, in the QL context, leave anonymisation as late as possible • Establish a standard page format and keep track of all anonymisation changes made in a standard format • Save and back-up both cleaned and cleaned and anonymised copies of transcripts

  37. Making the Long View THE LESSONS: RE-CONTEXTUALISING DATASETS • No two projects are the same, the issues involved in archiving and representing qualitative data will vary in detail • Different users will have very different contextualisation needs • When providing contextual data, establish boundaries between what your work and the work of future dataset users should be

More Related