12,637 papers · updated 18 Sept 2026livingmeta.ai
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Research theme

Productivity Effects

The Productivity Effects theme comprises 467 papers in this corpus published between 1994 and 2026. Work here is dominated by Empirical Study, Experimental, Survey. 5 open research gaps have been surfaced in this area.

Methodology profile

  • Empirical Study149 (32%)
  • Experimental99 (21%)
  • Survey40 (9%)
  • Mixed Methods39 (8%)
  • Case Study24 (5%)
  • Literature Review23 (5%)

Research domains

  • Research Productivity294 (63%)
  • Human-AI Collaboration122 (26%)
  • Doctoral Training24 (5%)
  • Data Analysis12 (3%)
  • Academic Writing7 (1%)
  • Scholarly Infrastructure3 (1%)

Frequent sub-topics

ChatGPT impact on student learning outcomes · 2ai_collaboration_modalities_and_job_interview_performance · 1ai_fatalism_and_student_outcomes · 1embodied_ai_presence_in_academic_study · 1Deep Structure Usage and information overload mitigation · 1developer productivity metrics in AI-assisted software development · 1knowledge hiding and job insecurity in agentic AI adoption · 1GenAI for survey design and rapid task learning · 1

Open research gaps

  • Not explicitly stated in the abstract
  • The authors identify the need for empirical testing of nine derived propositions and underscore gaps in understanding role trajectories for engineers over the next decade. They highlight implications
  • The abstract does not explicitly identify specific research gaps or future research directions.
  • Not explicitly stated in the provided abstract.
  • The abstract identifies a "severe deficit of diverse, large-scale trajectory data" as the bottleneck preventing progress toward autonomous software engineering, which the presented dataset aims to add

Representative papers

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