Bibliographic record
Abstract
Abstract This article applies Marx’s concept of the fetish generally and technological fetishism specifically to how digital ICTs are influencing the craft of journalism. A theoretical analysis of technological fetishism is linked to the findings of a 2013 survey among Canadian journalistic workers. These workers are found to hold mixed and often contradictory views on how digital technologies are shaping their work and profession. We understand ICTs as constitutive of journalism and as a technological fetish which mediates its development. In this context, the survey respondents are not ‘wrong’ to recognize that digital technologies seem to possess inherent powers. Because the fetishization of digital technologies is rooted in the social relations of contemporary journalism and neoliberal capitalism, redressing these is what needs to be strategically prioritized. Indeed, both critical thought (applied to the concept of technological fetishism) and political action are needed if the deleterious transformations taking place in journalism are to be modified and the democratizing potentials of digital ICTs fully realized.
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 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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.010 | 0.055 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".