The sociological imagination in studies of communication, information technologies, and media: CITAMS as an invisible college
Bibliographic record
Abstract
In this 2020 CITAMS special issue of Information, Communication & Society, we bring together an important body of work that draws on the sociological imagination to ask critical questions of our times. We selected nine papers that represent both the breadth of sociological work taking place within CITAMS as well as the diversity of its members. CITAMS is welcoming of a range of perspectives in more than one way. We welcome studies of a range of tools and practices. For example, Kadylak and Cotten (this volume) study the willingness of older adults to use six different emerging technologies in a single study including autonomous vehicles (AVs), assistive robots, Internet connected home appliances, Internet connected cameras for home monitoring, a smart home with a built-in personal digital assistant, and virtual reality (VR). Hoang, Blank, and Quan-Haase (this volume) deconstruct platform work and examine nine different types: “rideshare driving”, “delivery”, “online tasks”, “house/laundry cleaning”, or “other platform work”, “selling used goods”, “selling homemade goods”, “selling consumer brands”, and “selling other goods”. The special issue also showcases in-depth qualitative work. Brause and Blank (this volume) conduct in-depth interviews to learn about the role of Smart Speaker Assistants (SSAs) in the home. And Orr and Davis (this volume) conduct interviews with practitioners to find out about the ethics of artificial intelligence practitioners. Hargittai and colleagues develop a protocol for studying people’s awareness and understanding of algorithms in their interactions with online services including voice assistants, such as Alexa and Google Home. A key theme through all papers is a critical lens. Dodel and Mesch (this volume) look at automation. Boulianne, Koc-Michalska, and Bimber (this volume) examine the Facebook, Twitter, and television in protests. And finally Li and Luo (this volume) examine the roles of news media and Weibo in gender bias. Overall, the special issue provides theoretically-grounded, empirically-sound, and cutting-edge research and analysis.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| 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".