ASIS&T annual meeting pre‐conference activities: SIG/SI 8th annual research symposium a success!
Bibliographic record
Abstract
Abstract Editor's Summary Social informatics' past, present and future were the focus of the 8th annual SIG/SI Research Symposium at the 2012 ASIS&T Annual Meeting, with presenters from Europe, Canada and the United States. Papers on the past of social informatics explored its roots in the early 1980s and its domain organization reflected through bibliometric analysis. Current research topics described the influence of information and communication technologies as a contextual element that shapes experience and social interaction, knowledge sharing across boundaries in online communities and studying subjectivity in Web 2.0 research collaborations through Q methodology. Presenters considered the future of social informatics in terms of the influence of information and communication technologies on the economic order, aspects of information practice that demand attention and topics and frameworks for further research. Best paper awards were given for studies on evolving digital rights and urban immigrants' information tactics. Through the symposium and interaction with other SIGs, researchers were encouraged to take a broad view of social informatics to better understand its lessons, influences and future directions.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.168 | 0.105 |
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".