Shaken and stirred: ASIS&T 2011 attendee reactions to shaking it up: Embracing new methods for publishing, finding, discussing, and measuring our research output
Bibliographic record
Abstract
Abstract What does the Information Science community think about new, open methods for publishing, finding, discussing, and measuring our research output? This poster will summarize audience member participation and reaction to an ASIS&T 2011 panel discussing these issues. Reaction data will consist of several Likert‐scale and open‐ended responses. The data will be collected only a day or two before the poster is displayed: classification and visualization will be done openly to accomplish a rapid summary of the data. The tight timeline and attendees‐as‐data‐source will heighten the relevance of these exploratory results. Likert‐scale response distributions will be displayed in dot‐plots to facilitate additional Write‐On‐The‐Poster contributions from poster‐viewers, further increasing engagement. Through this process we hope to raise awareness of these new open methods, discuss their strengths and weaknesses for the Information Science community, experiment with new methods for face‐to‐face group scholarly communication, and build community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".