Bibliographic record
Abstract
This paper begins with a survey of the literature regarding a particular, yet ever more consequential and profitable, typology of digital labour: ‘free labour’ (Terranova, 2000, 2004), ‘unwaged immaterial labour’ (Brown and Quan Haase, 2012; Brown, 2013), and/or immaterial labour 2.0 (Coté & Pybus, 2007), to name a few of the more common terms. It then moves on to proffer a critical synthesis of this body of work so as to conclude with a much more theoretically nuanced definition of unwaged digital labour than that which has thus far been provided. In sum, the author argues that there are five central facets to unwaged digital labour that defines and differentiates it from its waged brethren. The first is that unwaged digital labour is fundamentally and inherently autonomous. Free of management oversight, the cooperative and creative capacities of content-generators produce massive amounts of digital artefacts that in the majority of cases also yield massive amounts of profit for the owners of Web 2.0 sites and services. The surplus value produced by this first facet refracts into the second. Following the work of Fuchs (2010, 2011, 2012, 2013), unwaged digital labour is (in the majority of circumstances) hyper-exploited. As has been argued elsewhere (Brown, 2013), this hyper-exploitation is the primary cause for recurrent ‘user’ uproar on Web 2.0 sites and services. This kind of exploitation, then, is met with the third facet of digital labour considered herein: resistance or struggle. Facile recourse to nebulous conceptions regarding the invasion of one’s privacy on eminently social networks no longer suffices in explaining these instances of ‘user’ uproar. Thus, a more nuanced consideration of the forms of resistance that occur on social media sites and services is offered. Similar, yet different, to its waged genus, the fourth facet of unwaged digital labour is that it is intrinsically collaborative, cooperative, and generative of social relationships. The differences that obtain between the orientation of the social relationships constituted by waged and unwaged digital labour respectively are indicative of political potentials that have up until this point been under-theorized. Thus, building on the four aforementioned facets, as well as the arguments put forth by Hardt and Negri regarding the biopolitical dimensions of ‘immaterial labour’ (2000, 2004, 2009), the fifth and most theoretically provocative facet is that this kind of labour is inspired, guided, and regulated by a radically different amalgam of biopolitical power relationships that point to the potentials of a commons-based political economy existing beyond the hyper-exploitative dimensions of capital.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.053 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".