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

Institutional Policy

The Institutional Policy theme comprises 617 papers in this corpus published between 2006 and 2026. Work here is dominated by Literature Review, Conceptual, Qualitative. 5 open research gaps have been surfaced in this area.

Methodology profile

  • Literature Review102 (17%)
  • Conceptual92 (15%)
  • Qualitative66 (11%)
  • Case Study64 (10%)
  • Policy Analysis56 (9%)
  • Mixed Methods53 (9%)

Research domains

  • AI Governance593 (96%)
  • Scholarly Infrastructure19 (3%)
  • Research Integrity3 (0%)
  • Peer Review2 (0%)

Frequent sub-topics

AI adoption in higher education institutions · 2organizational conditions for scaling AI adoption and overcoming pilot trap · 1educational technology governance and responsible AI implementation in learning environments · 1organizational discourse and generative AI adoption · 1multi-layer governance of generative AI-enabled platforms · 1adoption attitudes toward generative AI by experience level · 1Chief AI Officer role and organizational structure · 1AI curriculum alignment between academia and industry in Taiwan · 1

Open research gaps

  • The authors identify several gaps: (1) lack of formal AI policies among ASPPH members; (2) policies rarely address AI in community engagement contexts; (3) limited clarity on ownership and intellectua
  • The authors identify a critical gap: "no papers substantively addressed mission assurance: the process of ensuring that systems using AI continue to perform mission-essential functions under adverse c
  • The paper addresses a gap that "how these contestations unfold in practice remains underexplored," focusing on the dynamics of AI contestation and accountability-seeking processes.
  • Evidence on implementation, effectiveness, and governance of AI-assisted assessment in African ODeL institutions remains fragmented; limited empirical validation of AI techniques; need for robust eval
  • The abstract indicates that "less is known about citizens' considered views on this issue" regarding algorithmic decision-making in the public sector, and that the study aims to address this gap by pu

Representative papers

← Browse all papersPriority research agenda →