Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Citation (2016), "Editorial Board", Communication and Information Technologies Annual (Studies in Media and Communications, Vol. 11), Emerald Group Publishing Limited, Bingley, pp. vii-ix. https://doi.org/10.1108/S2050-206020160000011004 Publisher: Emerald Group Publishing Limited Copyright © 2016 Emerald Group Publishing Limited. Rebecca G. Adams University of North Carolina at Greensboro Ron Anderson University of Minnesota in Minneapolis Denise Anthony Dartmouth College Alejandro Artopoulos Universidad de San Andrés Jason Beech Universidad de San Andrés Grant Blank Oxford Internet Institute Geoffrey Bowker Bren School of Information and Computer Sciences Casey Brienza City University London Jonathan Bright Oxford Internet Institute Manuel Castells University of Southern California Mary Chayko Rutgers University Lynn Schofield Clark University of Denver Jennifer Earl University of Arizona Hernan Galperin Universidad de San Andrés Joshua Gamson University of San Francisco Blanca Gordo University of California at Berkeley Tim Hale Partners Center for Connected Health and Harvard Medical School David Halle University of California, Los Angeles Caroline Haythornthwaite University of British Columbia Anne Holohan Trinity College Dublin Heather Horst RMIT University Gabe Ignatow University of North Texas Samantha Nogueira Joyce Indiana University South Bend Vikki Katz Rutgers University Nalini Kotamraju Microsoft Dynamics Enterprise Resource Planning (ERP) Antonio C. La Pastina Texas A&M University Robert LaRose Michigan State University Sayonara Leal Universidade de Brasília Brian Loader University of York Monica Martinez Universidade de Sorocaba Noah McClain Illinois Institute of Technology Gustavo Mesch University of Haifa Sonia Virgínia Moreira Universidade do Estado r Gina Neff University of Washington Christena Nippert-Eng Illinois Institute of Technology Hiroshi Ono Texas A&M University CJ Pascoe University of Oregon Trevor Pinch Cornell University Anabel Quan-Haase University of Western Ontario Kelly Quinn University of Chicago Violaine Roussel University of Paris 8 Saskia Sassen Columbia University Sara Schoonmaker University of Redlands Markus S. Schulz University of Illinois at Urbana-Champaign Mike Stern University of Chicago Joseph D. Straubhaar University of Texas at Austin Andrea Hoplight Tapia Penn State University Simone Tosoni Catholic University of Milan Zeynep Tufekci University of North Carolina, Chapel Hill Keith Warner Santa Clara University Barry Wellman NetLab, University of Toronto Julie B. Wiest West Chester University of Pennsylvania Jim Witte George Mason University Book Chapters Communication and Information Technologies Annual [New] Media Cultures Studies in Media and Communications Communication and Information Technologies Annual [New] Media Cultures Copyright Page Editorial Board List of Contributors Acknowledgments Introduction: Volume 11 [New] Media Cultures Section I: Communicative Cultures On Violating One’s Own Privacy: N-adic Utterances and Inadvertent Disclosures in Online Venues Couples’ Use of Technology in Maintaining Relationships Section II: Media, Culture, and Identity Spectacles of Self(ie) Empowerment? Networked Individualism and the Logic of the (Post)Feminist Selfie You’ve Been Catfished: An Analysis of Postemotionalism in “Reality” Television and Audience Response on Twitter Cultures of Experimentation: Role-Playing Games and Sexual Identity Section III: Digital Public Cultures Twitter Sentiments: Pattern Recognition and Poll Prediction The Limits of Neoliberalism: How Writers and Editors Use Digital Technologies in the Literary Field The Role of Mass Media in the Transmission of Culture Section IV: Methods for Studying Media and Culture Virtual Tours: Enhancing Qualitative Methodology to Holistically Capture Youth Peer Cultures Sentiment Analysis of Polarizing Topics in Social Media: News Site Readers’ Comments on the Trayvon Martin Controversy About the Editors About the Authors
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.124 | 0.333 |
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 it