What Am I Worth?: Wage Security and the (In)secure Self
Bibliographic record
Abstract
Although income inequality is pervasive, a small number of organizations have taken it upon themselves to implement living wages for all of their employees. The literatures on the psychological experiences related to one’s income and to income inequality suggest that organizational efforts to reduce income inequality will also shape important social and psychological experiences for employees and impact their work; yet, neither employees’ experiences in light of these efforts nor how the organizational environment may shape their experiences is well understood. In this article we investigate how employees respond to a living wage initiative and the relationship between their responses and the broader organizational environment. Using both interviews and observations, we explore an organization’s implementation of a living wage in two locations. Our data reveal that the wage initiative and organizational culture were intertwined in ways that shaped employees’ approach to both their work and non- work lives, as employees experienced both security and insecurity. We show that beyond increasing wages, organizational leaders must reduce the potential for employees’ experience of insecurity by ensuring that they manage organizational cultural expectations appropriately and support employees’ growth in their work roles commensurately.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".