Methodology
How we analyze each lecture, what we measure, and why. Transparency is the point.
Process
Each lecture in the Predictive History corpus is analyzed through a systematic, repeatable pipeline:
- Transcript extraction — Auto-generated English subtitles downloaded via
yt-dlpin SRT format with timestamps. - AI analysis — The full transcript is provided to Claude Opus 4.6 with the analysis schema and scoring rubric. The model reads the entire transcript and produces a structured JSON assessment.
- Screencap extraction — For every timestamped item (quotes, rhetoric, predictions), a video frame is captured automatically via
ffmpeg. - Publication — JSON is rendered to static HTML. No editorial intervention beyond the rubric design.
Scoring Rubric
Each lecture is evaluated on seven axes, scored 1–5. Higher is better. Click any score on a lecture page to read the full justification.
| Axis | What it measures | 1 means | 5 means |
|---|---|---|---|
| Historical Accuracy | Are facts, dates, events, and causal claims correct per mainstream historiography? | Major errors | Solid throughout |
| Argumentative Rigor | Is reasoning logically sound? Are conclusions supported by the evidence presented? | Fallacious | Rigorous |
| Framing & Selectivity | Is the evidence cherry-picked? What's included versus excluded? | Highly selective | Balanced |
| Perspective Diversity | Are competing interpretations acknowledged? Counterarguments engaged? | Single narrative | Multiple perspectives |
| Normative Loading | How much moral judgment is embedded? Is the audience told what to think? | Heavily prescriptive | Descriptive / analytical |
| Determinism vs. Contingency | Is history presented as inevitable, or does the lecture acknowledge accident and agency? | Fully deterministic | Balanced contingency |
| Civilizational Framing | How are different civilizations characterized? Consistent hero/villain casting? | Strongly biased | Even-handed |
Limitations & Caveats
- AI analysis is not infallible. LLMs can misidentify rhetoric, misjudge accuracy on niche topics, or miss cultural context. Every justification is published so readers can evaluate the reasoning.
- Auto-generated transcripts contain errors. YouTube's speech-to-text occasionally garbles names, technical terms, and non-English words. Where a quote seems off, check the video.
- Scores reflect the rubric, not a verdict on the speaker. A low score on one lecture does not characterize the entire channel. Patterns emerge from the corpus, not from individual data points.
- This is content analysis, not mind-reading. We analyze what was said, how it was framed, and what was omitted. We do not speculate about the speaker's intentions or affiliations.
- The schema may evolve. If the rubric is refined, earlier analyses will be re-run and the version history published.
Reproducibility
Every claim in every report is traceable to a timestamp in a public YouTube video. The analysis schema is published — anyone can feed the same transcripts and rubric to an LLM and compare results.
Fair Use Notice
This site constitutes fair use under Section 107 of the U.S. Copyright Act (17 U.S.C. § 107) and analogous provisions in other jurisdictions. All original lecture content remains the property of its creator(s).
The four statutory factors:
- Purpose and character of the use. This project is transformative — it subjects publicly available lectures to systematic critical analysis, commentary, and research. No original content is reproduced for entertainment or as a substitute for the source material.
- Nature of the copyrighted work. The source lectures are published on YouTube, a public platform, and address matters of public interest (geopolitics, history, current affairs).
- Amount and substantiality. Only brief, timestamped quotations are reproduced to support specific analytical points. Individual video frames are used as contextual reference. Neither substitutes for viewing the original lectures.
- Effect on the market. This analysis does not compete with the original lectures and is likely to drive additional viewership to the source channel. No content is monetized.
All quoted material and screencaps are used solely for purposes of criticism, commentary, and scholarly analysis. Each item links or refers to the original public source.