Intergenerational Resonance Index (IRI) Dataset: YouTube Audience Comments on Intergenerational Podcast Content — INLM Empirical Validation Corpus (n=1,222, April 2026)

This dataset contains 1,222 YouTube comments collected viathe YouTube Data API v3 (April 2026) across five searchdomains targeting audience responses to intergenerationalpodcast and storytelling content:(1) intergenerational podcast older younger generation learning(2) grandparent grandchild stories wisdom podcast interview(3) baby boomer gen z conversation cultural heritage podcast(4) mentorship storytelling legacy older generation younger(5) intergenerational dialogue empathy community stories podcast The corpus is the primary empirical validation dataset forthe Intergenerational Resonance Index (IRI) — a novelcomputational metric measuring the proportion ofintergenerational resonance markers relative to totalemotional markers in audience-generated discourse. IRI = Resonance / (Resonance + Resistance Markers)where Resonance = Encounter + Reflection + Integration + Transmission markers Grounded in: Bandura (1977) social learning theory,Mezirow (1991) transformative learning, Allport (1954)contact hypothesis, and the Intergenerational NarrativeLearning Model (INLM, citation omitted blind review). KEY FINDINGS:- Mean IRI: 0.9773 (strongly resonant)- Encounter marker density: 0.7250/100 tokens (dominant)- Reflection marker density: 0.5871/100 tokens- Transmission marker density: 0.5659/100 tokens- Integration marker density: 0.5616/100 tokens- Resistance marker density: 0.0685/100 tokens (minimal)- Resonant(Encounter) cluster: 142 comments (30.0%)- Resonant(Reflection) cluster: 137 comments (28.9%)- Resonant(Integration) cluster: 94 comments (19.8%)- Resonant(Transmission) cluster: 91 comments (19.2%)- Resistant: 7 comments (1.5%) — negligible- Highest IRI domain: intergenerational dialogue/empathy (1.000)- Lowest IRI domain: older/younger generation learning (0.9551) THEORETICAL SIGNIFICANCE:All four INLM stages confirmed as distinct and present innaturalistic audience discourse. IRI = 0.9773 confirmsthat intergenerational podcast audiences produceoverwhelmingly resonance-dominant language. Near-equaldistribution across all four stages validates the INLMcyclical model empirically for the first time. Files:- iri_videos.csv: 50 unique videos metadata- iri_comments.csv: 1,222 raw comments- iri_results.csv: IRI scores + INLM stage annotation Method: YouTube Data API v3. Python 3.12, April 2026.