Inaugural issue perspectives on<i>Information and Learning Sciences</i>as an integral scholarly nexus
Bibliographic record
Abstract
Purpose Many of today’s information and technology systems and environments facilitate inquiry, learning, consciousness-raising and knowledge-building. Such platforms include e-learning systems which have learning, education and/or training as explicit goals or objectives. They also include search engines, social media platforms, video-sharing platforms, and knowledge sharing environments deployed for work, leisure, inquiry, and personal and professional productivity. The new journal,Information and Learning Sciences, aims to advance our understanding of human inquiry, learning and knowledge-building across such information, e-learning, and socio-technical system contexts. Design/methodology/approach This article introduces the journal at its launch under new editorship in January, 2019. The article, authored by the journal co-editors and all associate editors, explores the lineage of scholarly undertakings that have contributed to the journal's new scope and mission, which includes past and ongoing scholarship in the following arenas: Digital Youth, Constructionism, Mutually Constitutive Ties in Information and Learning Sciences, and Searching-as-Learning. Findings The article offers examples of ways in which the two fields stand to enrich each other towards a greater holistic advancement of scholarship. The article also summarizes the inaugural special issue contents from the following contributors: Caroline Haythornthwaite; Krista Glazewski and Cindy Hmelo-Silver; Stephanie Teasley; Gary Marchionini; Caroline R. Pitt; Adam Bell, Rose Strickman and Katie Davis; Denise Agosto; Nicole Cooke; and Victor Lee. Originality/value The article, this special issue, and the journal in full, are among the first formal and ongoing publication outlets to deliberately draw together and facilitate cross-disciplinary scholarship at this integral nexus. We enthusiastically and warmly invite continued engagement along these lines in the journal’s pages, and also welcome related, and wholly contrary points of view, and points of departure that may build upon or debate some of the themes we raise in the introduction and special issue contents.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.024 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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".