Parenting Journal · Volume 1 · Issue 3 · Licensed source edition
Developmental or evaluative? Understanding the impact of algorithmic evaluation on gig workers’ thriving at work
Originally published 2026-08-18 · Frontiers in Psychology
Frontiers Media SA · DOI 10.3389/fpsyg.2026.1899280 ↗
AI / system type
Developmental and evaluative algorithmic performance evaluation
Workplace evidenceExamines workers, organizations or AI at work. Participants are not necessarily parents; family benefits are not established by this evidence alone.
The AI connection
System or context examined: Developmental and evaluative algorithmic performance evaluation. Algorithmic management/control is not assumed to be machine learning or generative AI.
Why this reading matters
The reading brings developmental versus evaluative algorithmic assessment into a concrete discussion of humane work during technological change. It offers gig-worker questionnaire study evidence or analysis, not a promise of organizational or family benefit.
Workplace evidence
Work, care and the whole person.
The workplace lens is developmental versus evaluative algorithmic assessment. Source setting or population: 435 valid gig-worker responses analyzed with statistical, neural-network and necessity methods. Parenting and child-development outcomes are not inferred from the workplace evidence.
Examines workers, organizations or AI at work. Participants are not necessarily parents; family benefits are not established by this evidence alone.
Editorial reading guide · Respect
Does an algorithmic evaluation help me grow, or only tell me how I rank?
This gig-worker questionnaire study examines developmental versus evaluative algorithmic assessment. Its TRICK home is Respect, an editorial reading path rather than a claim that the paper tests the full framework.
Study context
435 valid gig-worker responses analyzed with statistical, neural-network and necessity methods
Age / stage: Adult workplace context; no child age range inferred
Read with three questions
- Does an algorithmic evaluation help me grow, or only tell me how I rank?
- What do this study’s design and population — 435 valid gig-worker responses analyzed with statistical, neural-network and necessity methods — allow you to infer about another workplace?
- When considering developmental versus evaluative algorithmic assessment, which decisions would need employee input before applying this reading to a working family’s circumstances?
Keep the limits in view
Observed evaluation styles are not randomly assigned; thriving and job-crafting associations do not prove a platform intervention’s effects.
The text below is the original article’s licensed repository edition. Its wording is not rewritten. Use the Paper Agent beside the text to locate evidence; open the source for figures, tables and complete context.
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Original authorship, publication date, journal and DOI are preserved. This issue’s TRICK placement and reading questions are editorial additions, not claims made by the original authors.
Xinyu Teng; Huan Tao; Chuntong Dong (2026). Developmental or evaluative? Understanding the impact of algorithmic evaluation on gig workers’ thriving at work Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2026.1899280
Permissions checked against the saved article notice; repository publication notices screened 2026-11-05. This is not a new peer-review decision. The source authors and publishers are not represented as endorsing this issue.