Beyond the Labels: Transforming LGBTQ+ Discoverability in the Philippine Library Landscape

Abstract

This study explores how subject access practices in academic libraries shape the visibility and discoverability of LGBTQIA+ knowledge, focusing on systemic gaps in representation within the Philippine academic landscape. Standardized subject headings and legacy classification schemes often fail to capture the nuanced complexity and evolving nature of LGBTQIA+ identities.

Analyzing over 1,400 bibliographic records across five library units at the University of the Philippines Diliman, this study employs a mixed-methods research design that combines computational natural language processing with qualitative insights from librarian interviews and user feedback. The methodology implements a three-stage computational pipeline: keyword extraction using RAKE and TF-IDF to generate high-impact descriptors, thematic exploration via K-Means clustering to reveal latent structures, and semantic retrieval using Cosine Similarity to build relationship-based pathways.

Findings reveal that while relevant resources are present, discoverability is severely constrained by generalized terminology, missing metadata (with ~73% of records lacking summaries), severe keyword flattening, and record duplication. To address these structural barriers, the paper proposes a responsive subject analysis framework that integrates localized vocabularies, multi-dimensional keywording practices, and AI-assisted metadata enrichment to establish equitable knowledge systems.