History Research Guide

Time layers in historical analysis:

1. LONGUE DUREE (centuries)
   - Geography, climate, demographics
   - Slow structural change
   - Example: Mediterranean trade routes, 500 BCE - 1500 CE

2. CONJUNCTURES (decades)
   - Economic cycles, social trends, institutional change
   - Medium-term patterns
   - Example: Rise and fall of Atlantic slave trade, 1500-1888

3. EVENTS (days to years)
   - Political events, battles, treaties, revolutions
   - Surface history, "l'histoire evenementielle"
   - Example: Fall of the Berlin Wall, November 9, 1989

Research tip: Strong historical arguments often operate across
multiple temporalities simultaneously.

# Example: Word frequency analysis across a corpus of historical documents
from collections import Counter
import re

def analyze_historical_corpus(texts: list, period_labels: list) -> dict:
    """
    Track keyword frequency across historical periods.
    Useful for tracing conceptual change (Begriffsgeschichte).
    """
    period_counts = {}
    for text, period in zip(texts, period_labels):
        words = re.findall(r'\b[a-z]+\b', text.lower())
        if period not in period_counts:
            period_counts[period] = Counter()
        period_counts[period].update(words)

    return period_counts

# Track usage of key concepts over time
def track_concept(period_counts: dict, concept_terms: list) -> dict:
    """Track normalized frequency of concept terms across periods."""
    results = {}
    for period, counts in sorted(period_counts.items()):
        total = sum(counts.values())
        concept_freq = sum(counts.get(term, 0) for term in concept_terms)
        results[period] = {
            "raw_count": concept_freq,
            "per_million": (concept_freq / total) * 1_000_000 if total > 0 else 0,
        }
    return results

# Example: Track "liberty" vs. "order" in political texts
# liberty_trend = track_concept(corpus, ["liberty", "freedom", "rights"])
# order_trend = track_concept(corpus, ["order", "authority", "stability"])

Applications of GIS in historical research:

- Mapping migration patterns (transatlantic slave trade routes)
- Spatial analysis of urban development (Paris renovation, 1853-1870)
- Battle reconstruction (troop movements, terrain analysis)
- Disease mapping (John Snow's cholera map, modernized)
- Trade network visualization (Silk Road, maritime routes)
- Land use change over time (enclosure, deforestation)

Tools: QGIS (free), ArcGIS, Google Earth Engine
Data: HGIS (Historical GIS), Natural Earth, GADM

Article structure (American Historical Review style):

1. OPENING (1-2 pages)
   - Narrative opening or striking primary source quotation
   - Situate within historiographical debate
   - Thesis statement (explicit and arguable)

2. BODY (15-25 pages)
   - Organized chronologically OR thematically
   - Each section advances the argument
   - Primary source evidence drives every claim
   - Engage with counterarguments and alternative interpretations
   - Footnotes: full citations, also substantive discussion

3. CONCLUSION (1-2 pages)
   - Restate thesis in light of evidence presented
   - Broader implications for the field
   - Open questions for future research

Citation style: Chicago Manual of Style (notes-bibliography)