The employer response to the guaranteed annual income
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract How do firms react when the whole labor force has access to a guaranteed income? One view argues that the guaranteed income is an employer subsidy, facilitating low wages and a ‘low-road’ industrial strategy. The second view suggests that in providing an alternative to work, the guaranteed income tightens labor markets and pulls wages up. This article examines the impact of an understudied social experiment from the late 1970s called the Manitoba Basic Annual Income Experiment, or Mincome. This research focuses on Mincome’s ‘saturation’ site, the town of Dauphin, Manitoba, where all residents were eligible for unconditional payments. Using an archived survey of local firms that inquires into wage rates, applications, hiring, and work hours, I find support for the second view. I close by examining the mechanisms behind the employer subsidy argument and considering the conditions under which a variety of income-support policies might increase or decrease wages, and more broadly, foster compromise or conflict in the labor market.
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.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.016 |
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 it