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Pushing for change

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Pushing for change .. data collection and analysis Dr Judy McGregor EEO Commissioner Human Rights Commission – PowerPoint PPT presentation

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Title: Pushing for change


1
Pushing for change.. data collection and analysis
  • Dr Judy McGregor
  • EEO Commissioner
  • Human Rights Commission

2
Data and the change process
  • Why collect data in the first place? Let alone
    analyse it?
  • Pace and quantity of information and access to it
    by technology has blurred the lines between fact,
    opinion, and rumour
  • Rise and rise of talkback information full of
    dangerous myths (women have made it in New
    Zealand, for example).

3
Value of quality data
  • Allows for informed debate
  • Community, group or individual exchange and
    empowerment through information
  • Provides comparisons-gender, ethnicity, age,
    Maori, Pacific, refugee and migrant communities,
    disabled people etc
  • Allows for measurement of progress over time
  • Pushes back against prejudice and stereotypes

4
What about NGOs and womens groups?
  • Data is useful internally and externally for
  • Reporting, CEDAW and other submissions
  • to support funding applications
  • to know who your clients are
  • to work out what members want
  • to examine trends and patterns (eg age of
    members).

5
Ten top tips
  • 1. Anyone can do it- small is beautiful and small
    and focussed is ideal. (You do not need to be a
    graduate in statistical regression)
  • 2. Look around for help-partners, academic
    researchers, report writers. (Judy and David,
    example)
  • 3. Do background research- someone has usually
    done something before you-All power to Google.

6
Ten top tips
  • 4. What is the question you want to answer? Need
    to work on what is called problem definition
  • It may be a how many?, a why?, a when?, a
    who?, a what? or all of them
  • Need the problem definition ideally BEFORE you
    gather the data.

7
The Census example
  • One over-arching research question
  • How many women on the boards of directors of the
    top 100 companies in NZ?
  • Problem definition is womens status in corporate
    governance

8
Have data, will use it?
  • Many organisations, groups and individuals
    collect/ hoard information for no purpose
  • A years worth of household power bills- what can
    they tell you? What do you want to know?
  • Five minute power bill exercise.

9
Power bill exercise
  • You have a years worth of power bills at home.
  • What questions could you usefully ask in relation
    to the bills?
  • The bills are the data. How can you use them to
    answer an important question?
  • What is an important question?

10
Ten top tips
  • 5. Always brainstorm what questions to ask
  • Whats new/ whats the current status of/ what
    are others asking us/ what are the gaps in our
    knowledge/ what would help us?
  • Four Ws and an H- who, when, what, why,
    how???????

11
Ten top tips
  • 6. Dont ever assume that no-one else has asked
    the question before you
  • To safeguard against research redundancy make
    sure that it hasnt been done before
  • Ask around, ring experts, check internet and
    libraries.

12
Ten top tips
  • 7. Work out the best method(s) to answer the
    question. For example, how many women on the
    board involves counting why there are so few
    women on the board - could involve interviews and
    surveys
  • Consider using more than one method because too
    much of one approach will not give us an entire
    picture.

13
Ten top tips
  • 8. Ensure you are systematic. For example a
    years power bills means 12 months not 10,11 etc
  • Need to adopt the rule that if another person was
    collecting they would collect the same
    material-apples and pears problem
  • Use of categories to collect data (grid sheets,
    forms, electronic template or spreadsheets)

14
Ten top tips
  • 9. Need a system to analyse the data so you get
    results. What does the data show? What do you
    look for and how?
  • 10 interviews of migrant women seeking work-
    standard questions.
  • Analysis is a way of making sense to see if there
    are common trends, patterns, themes. From chaos,
    jumble and ambiguity to clarity.

15
Ten top tips
  • A common template that allows entry of
    demographic data such as age, country of origin,
    how they came to NZ, educational level, family
    status etc
  • Details such as how long they looked for work,
    whether they retrained, did they suffer
    prejudice, which could be standard across the 10
    interviews.

16
Ten top tips
  • Add qualitative data-what the individual women
    said in the interview about their specific
    circumstances
  • Value of interview is the rich, womens voice it
    can provide of their own experience
  • Resonates with other women who agree, disagree
    (consonance factor or Womans Weekly)

17
Ten top tips
  • 10. Need to stay true to the data so that is
    persuasive, you can defend it, and you have kept
    faith with research participants
  • For example, dont claim more than what is
    revealed. If it is 10 migrant women only you
    cannot generalise to all migrant women

18
What do we mean by true to the data
  • Common research problems
  • Causation is very difficult to establish so do
    you mean correlation
  • For example, is A caused by B or does the data
    really only show that A is linked to B
  • Worsening child poverty caused by work incentive
    benefits or is linked to it?

19
Ten top tips
  • Keeping faith might mean showing back what you
    have gathered to the women you have gathered it
    from (Robin, Robyn, Robynne and Roban)
  • Consent forms for publication
  • Anonymity and confidentiality protocols
  • Verification

20
Plus one more tip
  • Need to plan how to release your research
  • Audiences, media, risk analysis
  • How will you speak, who will defend, how to
    arrange a chorus of support
  • If you go public prepare for aggressive,
    rottweiler questions and dismissive
    interviewers.

21
Who makes the news? exercise
  • Front page analysis- what is the question we want
    to answer?
  • What do we have to collect to answer it?
  • How do we analyse data collected?
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