Joint SIG/USE‐SIG/SI Research Symposium: Information Behavior in Workplaces
Bibliographic record
Abstract
EDITOR'S SUMMARY The 16th Annual Research Symposium for Special Interest Group/Information Needs, Seeking and Use (SIG/USE) was held in Copenhagen, Denmark. The focus of the symposium was information behavior and information practices as applicable to workplaces. As technology grows and shifts on a constant basis, so too must workplaces adapt how information is used and accessed. Newer generations in the workforce are expected to be able to learn many new skills, change careers several times and balance work life from home life with boundaries that are less clear than they used to be. Two presentations given by the 2014 and 2015 winners of the Elfreda A. Chatman Research Proposal Award started off the symposium. The 2016 winners of this award were announced by the awards committee chair, Wade Bishop, and included Karen Fisher of the University of Kentucky and Devon Greyson of the University of British Columbia, Canada.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.029 | 0.012 |
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".