‘A Workers’ Inquiry 2.0’: An Ethnographic Method for the Study of Produsage in Social Media Contexts
Bibliographic record
Abstract
In this paper, we propose a new ethnographic method for the study of produsage (Bruns 2008) in social media contexts. The proposed method is based on three lines of thought: Marx’s method of ‘A Workers’ Inquiry’, the autonomists’ method of co-research, and recent critical theory of Web 2.0. To show the applicability and usefulness of the proposed method, we first compare it to other Marxist inspired methodological approaches and then we describe a case study to illustrate the method’s diversity and its potential for providing new insights into the processes of produsage and the commodification of audiences as described in previous work by Smythe (1977), Bruns (2008), Cohen (2008), and Fuchs (2011). The case study consists of a critical examination of the mode of produsage as it takes place in Flickr, one of the largest photo-sharing communities on the Internet.
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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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.013 |
| Open science | 0.003 | 0.001 |
| 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".