Locating Televisual and Non‐Televisual Textual Sequences with Institutional Ethnography: A Study of Campus and Apartment CCTV Security Work
Bibliographic record
Abstract
There is a longstanding social scientific practice of focusing on verbal and written accounts as forms of data to the neglect of televisual materials. In this paper I address the above problematic by examining the productive power of video as a means of organizing social and work relations. Treating video as a form of text which is activated by human subjects and therefore an active constituent of organization in both local and extra‐local settings, I draw on interview and observation data collected from research conducted with closed‐circuit television (CCTV) surveillance camera operators engaged in various forms of security work. This research is an extension and utilization of institutional ethnography: a method of inquiry which problematizes social relations at the local site of lived experience, while examining how textual sequences coordinate consciousness, actions, and ruling relations. Taking up visual culture and the question of surveillance in institutional ethnography is a novel approach, and is ultimately important for de‐routinizing the organizational role camera surveillance plays in everyday life.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".