Bibliographic record
Abstract
We are pleased to introduce the first issue of 2021, which comprises many contributions from a wide range of research fields in communication and media studies, including digital communication, gender studies, media reception and effects, political communication, journalism research, and science communication. With authors from the universities of Zurich, Berne, and Fribourg, as well as from universities in Germany, Austria, Spain, Sweden, and Canada, this issue illustrates that SComS is a home for Swiss studies as well as international research. This is also highlighted by our advisory board, which was renewed in spring 2021. Its fourteen members are distinguished scholars with expertise in a wide range of research areas within communication and media studies. They also represent different Swiss language regions, neighboring countries of Switzerland, and other European countries (see more information on our website).With this issue, SComS has also renewed its editorial team and journal management. While Jolanta Drzewiecka and Silke Fürst are welcomed as new editors and Mike Meißner as new journal manager, SComS bids farewell to Sara Greco and Thomas Häussler, who served the editorial team for more than five years. Their engagement greatly contributed to SComS becoming a well-established open access journal within communication and media research.
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.064 | 0.052 |
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".