iSchool Student Research Journal, Vol.9, Iss.2
Bibliographic record
Abstract
Twitter Facilitates Professional Discussions."Hicks, recently awarded a grant for research into this crucial arena of discourse on the nature and influence of Twitter in the context of the LIS field, shares some compelling questions the research will address.Hicks' contribution discusses the potential of Twitter as a professional tool for increasing inclusion and embracing diversity in the LIS field.Speaking to the profession's values of diversity and intellectual freedom, Hicks identifyies the need for professional organizations to articulate these professional values within the context of emerging forms of online communication and community-building tools, such as Twitter.Hicks' research will contextualize and tease out core debates within the LIS profession regarding Twitter as a platform and how to align professional values with social media engagement.Hicks' work could not be any more on point with key questions in our field and professional community and it is a true pleasure to share a preview.Author Ali N. Sadik-Ogli's evidence summary reviews a pioneering 2018 study focusing on the circulation and collection of zines from the perspective of zine authors themselves.This study addresses the value of inclusive circulation and collection that incorporates a broader perspective of types of records and content, such as born-digital, self-produced and limited-edition physical productions.In the increasingly virtual and fluid world of artistic and culture production, expanding our vision as LIS professionals of how to increase equity of access while ensuring proper attribution and means for supporting creators is a delicate balance worthy of exploration.
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".