Bibliographic record
Abstract
The task of this paper is to point out the relevance of Karl Marx for Internet Studies. Marxian concepts that have been reflected implicitly or explicitly in Internet Studies include: (1) dialectics; (2) capitalism; (3) commodity/commodification; (4) surplus value, exploitation, alienation, class; (5) globalization; (6) ideology/ideology critique; (7) art and aesthetics; (8) class struggle; (9) commons; (10) public sphere; (11) communism. The paper provides a literature overview for showing that, and how, Marxian concepts have been used in Internet Studies. Internet Studies to a certain extent analyse the Internet, economy and society in Marxist-inspired studies terms, yet do not acknowledge the connection to Marx and thus seem superficial in their various approaches discussing capitalism, exploitation and domination. We argue that it is time to actively remember that Marx is the founding figure of Critical Studies and that Marxian analyses are crucial for understanding the contemporary role of the Internet and the media in society.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.052 | 0.019 |
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".