“Why I Left BuzzFeed”: Alienation, YouTube, and Creative Labour in the Digital Age
Bibliographic record
Abstract
Digital media companies on YouTube, exemplified by BuzzFeed, reinforce the perception of employment in the creative industries as an ideal opportunity for young millennials to make money “doing what they love.” In 2016, dozens of videos made by former BuzzFeed employees announcing their departures from the company went viral, challenging this view and granting the public unprecedented insight into the company's labour practices. BuzzFeed thus serves as a valuable case study for digital labour in the contemporary creative industries during a time when formal companies, individual creators, and unpaid users compete for viewership on the platform. This research paper reveals and critically engages with the tradeoffs that creative workers face when negotiating the benefits of working for a company, versus “going independent.” Using Marx’s theory of alienation to analyze “Why I Left BuzzFeed” videos, this paper argues that the option for professional creative workers to become independent creators on YouTube represents a shift towards the ideal of “non-alienated labour.” This article concludes by examining how, despite this shift, independent creative workers are still subsumed under capital.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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".