A Critical Examination of a Third Employment Category for On-Demand Work (In Comparative Perspective)
Bibliographic record
Abstract
A number of lawsuits in the United States are challenging the employment classification of workers in the platform economy. Employee status is a crucial gateway in determining entitlement to labor and employment law protections. In response to this uncertainty, some commentators have proposed an “intermediate”, “third,” or “hybrid” category, situated between the categories of “employee” and “independent contractor.”\nAfter investigating the status of platform workers in the United States, the authors provide snapshot summaries of five legal systems that have experimented with implementing a legal tool similar to an intermediate category to cover non-standard workers: Canada, Italy, Spain, Germany, and South Korea. These various legal systems have had diverse results. There has been success in some instances, and unintended consequences in others.\nAccordingly, the authors recommend proceeding with caution in considering the creation of a third category. That is due to the risk of arbitrage between the categories, and the possibility that some workers will lose rights by having their status downgraded into the third category. Cherry and Aloisi posit employee status as the default rule for most gig workers. The authors propose an exception for those working on a de minimis basis or those engaged in volunteerism for altruistic reasons.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Open science | 0.000 | 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".