Reference health

The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: Evidence from Field Experiments

https://doi.org/10.2139/ssrn.3550887
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38/38 checkable references clean · checked 2026-08-06

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

19 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 38 checked references that resolve
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“I had so much it didn’t seem fair”: Eight-year-olds reject two forms of inequity
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Does Working from Home Work? Evidence from a Chinese Experiment *
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The Labor Illusion: How Operational Transparency Increases Perceived Value
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Task-Dependent Algorithm Aversion
resolves10.1016/j.jm.2003.04.001
The Fairness of Decision Rules
resolves10.1038/nature05651
Egalitarian motives in humans
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Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them
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A Behavioral Account of the Labor Market: The Role of Fairness Concerns
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A Theory of Fairness, Competition, and Cooperation
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Dimensions of Mind Perception
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Feeling robots and human zombies: Mind perception and the uncanny valley
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The Behavioralist Visits the Factory: Increasing Productivity Using Simple Framing Manipulations
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Team Familiarity, Role Experience, and Performance: Evidence from Indian Software Services
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Behavioral Empirics and Field Experiments
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How Scheduling Can Bias Quality Assessment: Evidence from Food-Safety Inspections
resolves10.1111/1472-9296.00009
Performance Related Pay: The Importance of Fairness
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Heuristic Thinking in Patient Care
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Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads
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Resistance to Medical Artificial Intelligence
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When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions
resolves10.1126/science.aax2342
Dissecting racial bias in an algorithm used to manage the health of populations
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The 19 references without a DOI — listed, not checked
no DOI — not checkedref9
no DOI — not checkedref12
no DOI — not checkedJustice at the millennium: a meta-analytic review of 25 years of organizational justice research
no DOI — not checkedref15
no DOI — not checkedEconomics, fairness and algorithmic bias. Preparation for
no DOI — not checkedref18
no DOI — not checkedAlgorithm aversion: People erroneously avoid algorithms after seeing them err
no DOI — not checkedStrategically giving service: The effect of real-time information on service efficiency
no DOI — not checkedAlgorithmic fairness
no DOI — not checkedref35
no DOI — not checkedThe sense of control as a moderator of social class differences in health and well-being
no DOI — not checkedref39
no DOI — not checkedFrontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases
no DOI — not checkedSex differences in value priorities: cross-cultural and multimethod studies
no DOI — not checkedPredicting human discretion to adjust algorithmic prescription: A large-scale field experiment in warehouse operations
no DOI — not checkedThe psychology of procedural justice: A test of the group-value model
no DOI — not checkedIs more fairness always preferred? self-esteem moderates reactions to procedural justice
no DOI — not checkedref55
no DOI — not checkedOperational risk management: Team-based effort and incentive bonus
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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