Academic libraries increasingly present collaboration as evidence of institutional value, linking partnerships with faculty, research offices, student services, cultural institutions, community organizations, and professional bodies to claims about student success, research support, equity, open scholarship, cultural preservation, and public engagement. Yet public library documents often blur the distinction between collaborative activities, countable outputs, user or institutional outcomes, and longer-term impact. This study examines how academic library public documents construct, evidence, and legitimate claims of collaborative impact. Using qualitative comparative document analysis, it analyzes public annual reports, strategic plans, impact and assessment documents, and professional frameworks at the level of the impact claim rather than the whole document. The article develops a claim–evidence–legitimation framework that codes claims by impact level, evidence type, claim strength, impact domain, partnership domain, beneficiary, evidentiary adequacy, and legitimation mode. The analysis shows how collaborative impact is often framed through student success, access, research support, equity, public value, and institutional alignment, while the evidence used to substantiate these claims varies substantially in strength and fit. The article argues that the central assessment problem is not simply the absence of metrics, but the mismatch between claim strength and evidentiary support. It contributes a framework for distinguishing symbolic, output-based, outcome-oriented, and transformative collaborative impact claims and offers practical guidance for aligning public reporting with the level of evidence required by different kinds of impact claims.

Thesis Research

Analisis prediksi dini risiko serangan jantung menggunakan algoritma K-Nearest Neighbor (KNN) berbasis data lifestyle dan medis. Dataset yang digunakan adalah Heart Attack Prediction in Indonesia dari Kaggle dengan total 9.407 sampel data.

TUBES CRM