Introduction to the Special Issue. Qualitative Analysis Conference 2011: Contemporary Issues in Qualitative Research
Bibliographic record
Abstract
T he community of scholars that attends the Qualitative Analysis Conference in Canada each year has grown considerably since the event's inception in 1984.The inaugural meeting at the University of Waterloo in Ontario, Canada saw a small number of committed qualitative researchers gather for a conference that was first called, "Deviance in a Cross-Cultural Context."Over the last 28 years, the Qualitatives has become an annual touchstone for qualitative researchers in Canada and abroad -attracting participants from all regions of Canada, as well as the United States, Mexico, Britain, France, Germany, Norway, Poland, Australia and Hong Kong.Last year, nearly 200 people attended the three-day conference.The theme of the 2011 conference, Contemporary Issues in Qualitative Research, was established to focus attention on both the application of qualitative methods and the debates surrounding qualitative inquiries, with a consideration of the implications for interdisciplinary standards for systematic qualitative research.The theme was broad enough to ensure a spectrum of papers from different disciplinary, theoretical, and methodological orientations.We encouraged presenters to focus their attention on current issues facing qualitative research, and to explore new and enduring challenges to qualitative methodologies, such as research standards, the inte-
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.211 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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; both teacher heads agree on what is shown here.
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".