Researching chaotically
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paper given by Jim Bright and Robert Pryor at the CDAA international careers conference in Cairns, April 29th 2011
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Researching chaotically
- 1. Researching Patterns of Career Behaviour Chaotically, Constructively, Narratively, Numerately and Beyond Dr Jim Bright & Dr Robert Pryor ACU
- 2. Existing methods • Quantative methods • E.g. Bright, Pryor, Chan, Rijanto (2009), Bright • Scales - LRI, CPI (Bright Pryor, 2005) • measuring not stability, but people’s tendency to deal with change, opportunity, chance © Jim Bright & Robert Pryor 2011
- 3. Constructivist methods • Can look at much more complex patterns • Emerging patterns in career • Narrative (a literary collage, Snowden, 2010) • Collage (Adams, 2003; Loader, 2010, 2011) • Metaphor (Amundson, 2010) • Journalling • Card-sorts - Magic Happens, Signposts • triggers to elicit stories, accounts, meaning • CIS - interests on card sort - what do you mean by your responses? © Jim Bright & Robert Pryor 2011
- 4. Analysing Patterns • Tags (John L. Holland, 1995) • Counting of features • Symmetries (Cf Fractal) • c.f. emergent themes • In stories • generalised abstractions to relate stories to other stories • Archetypical narratives © Jim Bright & Robert Pryor 2011
- 5. Stories, anecdotes or fragments? • resist over synthesis that can occur in construction of stories • raw accounts, unembellished, fragmentary - verbal collages • simple tags • e.g. Snowden’s Sensemaker Suite © Jim Bright & Robert Pryor 2011
- 6. Non linearity • Sudden and/or disproportionate change • linear stats cannot detect • weak signals • feelings, uncertain signals, almost certain signals and exact signals. (Turo Uskali, 2005,Innovation Journalism, Vol 2 No 11 2005) © Jim Bright & Robert Pryor 2011
- 7. Process & Outcomes • need to privilege processes as well as outcomes © Jim Bright & Robert Pryor 2011
- 8. Grounded theory (Glaser, 1992; Strauss & Corbin, 1998) • works backward from traditional theory research • theoretical concepts are generated from the field rather tested in the field • usually qualitative but can be quantitative • involves going out into the “field” to collect data on repeated occasions • in between occasions data are analysed to assist in the derivation of categories (ie units of information) • data are continued to be gathered until categories are “saturated” • sampling is purposive rather than representative • theoretical sampling – to assist the researcher formulate theory/generate concepts/identify emergent patterns • seems particularly appropriate to investigating complex phenomena • allows for the emergence of patterns, concepts and theoretical insights © Jim Bright & Robert Pryor 2011
- 9. Vocational Interests researched using grounded theory approach • Take “extreme categories” – like/dislike • Personal constructs – to generate patterns of interpretation randomly • Allow individual to generate additional items/cards • Explore • personal meanings • contingency perceptions • origins of preference • Capture across different groups © Jim Bright & Robert Pryor 2011
- 10. Possible strengths • Explicit procedures for generating concepts through research • A research method which is both systematic and flexible • Does not presuppose how the pattern in the data collected will emerge • Has the potential to be translated back into quantitative form for comparison and generalisability © Jim Bright & Robert Pryor 2011
- 11. Possible limitations • Something has to be assumed/ presupposed before any project can be initiated • The challenge to induce patterns out of the data may be too researcher dependent • There may be an arbitrariness or practical artificiality to deciding when categories are saturated. © Jim Bright & Robert Pryor 2011
- 12. Symbiotic Processes • Need BOTH quantitative and qualitative approaches © Jim Bright & Robert Pryor 2011
- 13. Bringing it back • Bring back story • to implementation • to reality • to world of action • At some point got to do something/ make a decision (Lenz, 2008) © Jim Bright & Robert Pryor 2011
- 14. Conclusions • Chaos & complexity demand new methods - patterns -narratives, anecdotes, collages, metaphors • Complement & extend existing methods • What is the pattern in the numbers & how many patterns are similar? • Understanding personal meaning & social connection © Jim Bright & Robert Pryor 2011
Notes de l'éditeur
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- The indexer is asked to name their story; such names turn out to be highly\nsignificant and often contain more meaning than the content itself.\n\n Why was the story told? (to attack, to defend, to educate, to\nentertain, to influence, to inform, to uplift or unclear); Was the story sacred or\neveryday? (this is normally elaborated in context but is important); What was the\ntellers relationship to the story? (Central character, reported by witness, hearsay\nor gossip)\nKeywords were introduced partly to avoid arguments with more traditional\napproaches, but have proved useful and allow standard capabilities such as tag\nclouds to be used to good effect. A switch of the standard question from What\nare the key words in this story to What are the key words you would associate with\nstory produced a significant reduction in the percentage of key words contained in\nthe original content; representing another criticism of semantic analysis.\nA free text field is then provided to allow additional descriptions or explanations\nto be provided if required. This can be useful if the content is not textual in\nnature but is generally useful.\n
- Too neat, ties up loose ends, over-reaches in attempts to account for all, \n
- Igor Ansoff (1975, 1980a, 1980b, 1990) was first to argue that information has two\nextreme levels: strong signals and weak signals.7 In his opinion, strong signals\nwere “sufficiently visible” and “concrete”, and weak signals are “imprecise early\nindications about impending impactful events”8. Ansoff believed that weak signals\nmay mature over time and become strong signals. His five different stages of\nsignals were:\n1) the sense of a threat/opportunity is felt;\n2) the source of the threat/opportunity is known;\n3) the shape of the threat/opportunity becomes concrete;\n4) the response strategies are understood;\n5) the outcome of the response is predictable.\n
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