Story completion for qualitative research
Bibliographic record
Abstract
**PDF Version** Print Version also available via Curran soon These proceedings represent the work of researchers participating in the 17th European Conference on Research Methodology for Business and Management Studies (ECRM) which is being hosted this year by Università Roma TRE, Rome, Italy on 12-13 July 2018. ECRM is a recognised event on the international research conferences calendar and provides a valuable platform for individuals to present their research findings, display their work in progress and discuss advances in the area of Research methodology within the Business Studies Domain. It provides an important opportunity for researchers and practitioners to come together to share their experiences in this varied and expanding field. This year the conference has had a focus on Interventionist Research which has been highlighted in the pre-conference workshops and keynote presentations. The first day will be opened with a keynote presentation by Dr. John Dumay from Macquarie University in Sydney, Australia, who will be speaking on “Getting your Hands Dirty: A Critical Approach to Interventionist Research”. In the afternoon there will be a speech by Prof. Anna Linda Musacchio Adorisio from Copenhagen Business School, Denmark entitled “Broadening the Context: Interpretive Lenses for Business Research”. Prof Paola Torrioni of the University of Turin, Italy will then speak on the second day about “Mixed Method Research”. With an initial submission of 167 abstracts, after the double blind, peer-review process there are 57 academic Research papers, 5 PhD Research papers published in these Conference Proceedings. These papers represent truly global research in the field, with contributions from Australia, Belgium, Brazil, Canada, Czech Republic, Denmark, Finland, Germany, Iran, Ireland, Italy, Lithuania, New Zealand, Poland Portugal, Russia, Slovakia, South Africa, Sweden, Taiwan, Thailand and UK.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.143 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.243 | 0.041 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".