Bibliographic record
Abstract
This paper contributes to the union renewal literature by examining the union voting propensity of workers in the high-tech tertiary sector of videogame development toward different forms of unionization. We used exclusive data from a survey of videogame developers (VGD) working primarily in Anglo-Saxon countries. When looking at the factors related to voting propensity, our data indicated that the type of unionism matters and that industry/sectoral unionism is an increasingly salient model for project-based knowledge workers. This is an important policy dimension given that the legal structures and norms in Anglo-Saxon countries still tend to support decentralized enterprise-based unionism. It is also important for unions insofar as their organizing tactics remain geared toward a shop-by-shop approach or, at least, a localized geographical approach. Although additional work is required, our analyses lends support to the argument that high-commitment and high-involvement workplaces can engender a desire for collective representation and voice such as is offered through unionization. Whether this is because such workplaces step over a breaking-point line where the requirement for full alignment with employer goals becomes untenable and a source of discontent, whether this represents the existence of dual commitment where a representative agent like a union is seen as necessary to protect the work that people love, or whether there is a combination of these forces is not yet clear, but it is a critical area of future study for project-based knowledge workers.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".