Ayushnangia/ana_v2.1_final_full

Unified UNSC Resolutions Dataset - Complete Documentation

File: unified_unsc_resolutions.jsonl Format: JSON Lines (one JSON object per line) Total Records: 2,767 resolutions Date Range: January 1946 - December 2024 (79 years) File Size: ~520 MB

---

📋 Executive Summary

This unified dataset combines data from three source files to create the most comprehensive UNSC resolutions database:

• Base: File 1 (CR-UNSC_2024-05-19_ALL_CSV_FULL.csv) - 2,722 resolutions (1946-2024 Jan) with full text and metadata
• Enrichment 1: File 2 (2025_7_21_sc_voting.csv) - Individual country voting data (complete 2024)
• Enrichment 2: File 3 (sc_voting_with_drafts_final.jsonl) - Extracted draft PDF text (complete 2024)
• 2024 Extension: 45 additional resolutions (Feb-Dec 2024) from Files 2 & 3 only

🎯 Key Statistics:

• ✅ 100% have complete metadata from File 1
• ✅ 100% have individual member state votes (File 2)
• ✅ 97.7% have draft symbols (File 1)
• ✅ 97.3% have draft text (96.4% from File 1, 62.9% from File 3)
• ✅ 99.9% have multilingual text (6 languages)
• ✅ 100% have URLs to UN documents

🔧 Data Quality Enhancements Applied:

1. Symbol Normalization - Fixed formatting mismatch between source files

   • Achieved 100% member state vote coverage (up from 75.8%)
   • See: MERGE_FIX_NOTES.md

2. Draft Symbol Addition - Added draft symbol field from File 1

   • Improved draft symbol coverage to 97.7%

3. Vote Type Simplification - Merged "X" (Not Participating) into "A" (Abstain)

   • Simplified from 4 vote types to 3 (Y/N/A)
   • See: CONVERSION_X_TO_A_NOTES.md

4. 2024 Completion - Added 45 missing resolutions (Feb-Dec 2024)

   • Extended dataset to full year 2024 using Files 2 & 3
   • All 46 resolutions from 2024 now included (S/RES/2722 to S/RES/2767)
   • Note: Feb-Dec 2024 records lack File 1 data (full text, thematic coding)

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📊 Dataset Structure

Top-Level Organization

Each resolution is a single JSON object with 18 top-level sections:

{
  "identifiers": {...},           // FROM FILE 1
  "dates": {...},                 // FROM FILE 1
  "meeting": {...},               // FROM FILE 1
  "content": {...},               // FROM FILE 1
  "thematic_coding": {...},       // FROM FILE 1 (UNIQUE)
  "resolution_text": {...},       // FROM FILE 1
  "resolution_text_multilingual": {...},  // FROM FILE 1
  "draft_from_file1": {...},      // FROM FILE 1
  "draft_pdf": {...},             // FROM FILE 3 (UNIQUE)
  "meeting_text": {...},          // FROM FILE 1
  "voting_totals": {...},         // FROM FILE 1
  "member_state_votes": [...],    // FROM FILE 2 (UNIQUE)
  "geographic": {...},            // FROM FILE 1
  "urls_resolution": {...},       // FROM FILE 1
  "urls_draft": {...},            // FROM FILE 1
  "urls_meeting": {...},          // FROM FILE 1
  "urls_records": {...},          // FROM FILE 1
  "administrative": {...}         // FROM FILE 1
}

Total Fields: ~108 flattened fields

---

📖 Section-by-Section Breakdown

1. IDENTIFIERS (7 fields) - FROM FILE 1

Core identification information for each resolution.

"identifiers": {
  "symbol": "S/RES/2758(2024)",           // Primary key: Resolution symbol
  "res_no": 2758,                         // Resolution number only
  "year": 2024,                           // Year of adoption
  "doc_id": "S_RES_2758_2024_EN_GOLD.txt", // Document ID
  "body": "S",                            // UN Body (Security Council)
  "doctype": "RES",                       // Document type (Resolution)
  "call_number": "UNS(01)/R3"             // Library call number
}

Source: File 1 (columns: symbol, res_no, year, doc_id, body, doctype, call_number) Coverage: 100% (2,722/2,722)

---

2. DATES (2 fields) - FROM FILE 1

Temporal information about the resolution.

"dates": {
  "date": "2024-01-10",          // Date resolution was adopted
  "vote_date": "2024-01-10"      // Date of vote (may differ from adoption)
}

Source: File 1 (columns: date, vote_date) Coverage: 100%

---

3. MEETING (2 fields) - FROM FILE 1

Information about the Security Council meeting.

"meeting": {
  "meeting_record": "S/PV.9521",  // Meeting record symbol
  "meeting_no": 9521.0            // Meeting number
}

Source: File 1 (columns: meeting_record, meeting_no) Coverage: 100%

---

4. CONTENT (7 fields) - FROM FILE 1

Descriptive content about the resolution.

"content": {
  "title": "Security Council resolution 2758 (2024) [on extension of mandate...]",
  "summary": "Summary text of the resolution...",
  "topic": "Extension of mandate for UN mission...",
  "subjects": "PEACEKEEPING OPERATIONS|SOUTH SUDAN|UN MISSION IN SOUTH SUDAN",
  "agenda_information": "Reports of the Secretary-General on the Sudan and South Sudan",
  "other_titles": "Alternative title formats...",
  "notes": "Additional notes about the resolution..."
}

Fields:

• title: Official title from UN records
• summary: Executive summary (when available)
• topic: Main topic classification
• subjects: Pipe-separated keywords
• agenda_information: Agenda item description
• other_titles: Alternative title formats
• notes: Additional contextual notes

Source: File 1 (columns: title, summary, topic, subjects, agenda_information, other_titles, notes) Coverage: 100%

---

5. THEMATIC CODING (8 fields) - FROM FILE 1 ⭐ UNIQUE

Boolean flags for thematic classification. This is UNIQUE to File 1 and invaluable for research.

"thematic_coding": {
  "chapter6": false,      // Chapter VI: Pacific Settlement of Disputes
  "chapter7": true,       // Chapter VII: Threats to Peace, Acts of Aggression
  "chapter8": false,      // Chapter VIII: Regional Arrangements
  "human_rights": true,   // Human rights related
  "peace_threat": true,   // Addresses threat to peace
  "peace_breach": false,  // Addresses breach of peace
  "self_defence": false,  // Self-defense related
  "aggression": false     // Act of aggression related
}

Statistics:

• 34.2% (932 resolutions) have at least one thematic tag
• Chapter VII (Peace & Security): 896 resolutions (32.9%)
• Human Rights: 791 resolutions (29.1%)
• Peace Threat: 421 resolutions (15.5%)
• Chapter VIII (Regional): 57 resolutions (2.1%)
• Chapter VI (Pacific Settlement): 9 resolutions (0.3%)
• Peace Breach: 5 resolutions (0.2%)

Source: File 1 (columns: chapter6, chapter7, chapter8, human_rights, peace_threat, peace_breach, self_defence, aggression) Coverage: 34.2% have tags (rest are null/false)

---

6. RESOLUTION TEXT (6 fields) - FROM FILE 1

Full English text of the adopted resolution with statistics.

"resolution_text": {
  "text_en": "Full text of the resolution in English...",
  "char_count": 5432,      // Character count
  "page_count": 3.0,       // Number of pages
  "sentence_count": 45,    // Number of sentences
  "token_count": 1203,     // Number of tokens/words
  "type_count": 456        // Number of unique word types
}

Source: File 1 (columns: text, nchars, npages, nsentences, ntokens, ntypes) Coverage: 100% Average Resolution Length:

• ~4,500 characters
• ~3 pages
• ~900 words

---

7. RESOLUTION TEXT MULTILINGUAL (5 fields) - FROM FILE 1

Full resolution text in the 5 other official UN languages.

"resolution_text_multilingual": {
  "text_ar": "Arabic text...",     // Arabic
  "text_es": "Spanish text...",    // Spanish (Español)
  "text_fr": "French text...",     // French (Français)
  "text_ru": "Russian text...",    // Russian (Русский)
  "text_zh": "Chinese text..."     // Chinese (中文)
}

Source: File 1 (columns: text_ar, text_es, text_fr, text_ru, text_zh) Coverage: 99.9% (2,719/2,722) Note: This is why the file is 514 MB. Remove these fields to reduce to ~100 MB.

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8. DRAFT FROM FILE 1 (2 fields) - FROM FILE 1

Draft resolution text and symbol as stored in File 1.

"draft_from_file1": {
  "draft_symbol": "S/2024/12",              // Draft document symbol
  "text_draft": "Full text of the draft resolution..."
}

Source: File 1 (columns: draft, text_draft) Coverage:

• Draft symbol: 97.7% (2,659/2,722)
• Draft text: 96.4% (2,623/2,722)

---

9. DRAFT PDF (5 fields) - FROM FILE 3 ⭐ UNIQUE

Draft resolution text extracted from PDF files. This is UNIQUE to File 3 and provides additional draft coverage.

"draft_pdf": {
  "draft_symbol": "S/2024/12",              // Draft document symbol
  "draft_text": "Extracted PDF text...",    // Full extracted text
  "draft_char_count": 1664,                 // Character count
  "draft_page_count": 1,                    // Number of pages
  "draft_filename": "draft_S_2024_12.pdf"   // Original PDF filename
}

Source: File 3 (field: draft_pdf) Coverage: 62.9% (1,712/2,722) Quality: Only includes drafts where text extraction succeeded (no errors)

Combined Draft Coverage:

• Either File 1 OR File 3: 97.3% (2,648/2,722)
• Both sources: 37.8% (1,029/2,722)
• No draft at all: 2.7% (74/2,722)

upFull text of the meeting record/verbatim.

"meeting_text": {
  "text": "Full meeting record text..."
}

Source: File 1 (column: text_meeting) Coverage: Varies

---

11. VOTING TOTALS (7 fields) - FROM FILE 1

Aggregate voting statistics (totals only, not by country).

"voting_totals": {
  "vote_yes": 15,              // Total yes votes
  "vote_no": 0,                // Total no votes
  "vote_abstention": 0,        // Total abstentions (includes not participating)
  "vote_nonvote": 0,           // Always 0 (merged into vote_abstention)
  "vote_total": 15,            // Total member states
  "vote_detail": "...",        // Detailed vote description
  "vote_summary": "Adopted unanimously"  // Vote summary
}

Source: File 1 (columns: vote_yes, vote_no, vote_abstention, vote_nonvote, vote_total, vote_detail, vote_summary) Coverage: 100%

Note on vote_nonvote: Originally distinguished "not participating" from "abstain", but these have been merged into vote_abstention for simplicity. vote_nonvote is kept as a legacy field (always 0).

Math Check: vote_yes + vote_no + vote_abstention = vote_total

---

12. MEMBER STATE VOTES (array) - FROM FILE 2 ⭐ UNIQUE

Individual member state votes. This is UNIQUE to File 2 and essential for studying voting patterns.

"member_state_votes": [
  {
    "code": "CHN",                  // 3-letter country code
    "name": "CHINA",                // Country name
    "vote": "Y",                    // Vote: Y/N/A (Yes/No/Abstain)
    "permanent_member": true        // Is P5 member?
  },
  {
    "code": "USA",
    "name": "UNITED STATES",
    "vote": "Y",
    "permanent_member": true
  },
  {
    "code": "FRA",
    "name": "FRANCE",
    "vote": "Y",
    "permanent_member": true
  },
  {
    "code": "GBR",
    "name": "UNITED KINGDOM",
    "vote": "Y",
    "permanent_member": true
  },
  {
    "code": "RUS",
    "name": "RUSSIAN FEDERATION",
    "vote": "Y",
    "permanent_member": true
  },
  // ... 10 non-permanent members
]

Vote Types:

• Y = Yes (voted in favor)
• N = No (voted against)
• A = Abstain (abstained from voting or not participating)

Source: File 2 (columns: ms_code, ms_name, ms_vote, permanent_member) Coverage: 100% (2,722/2,722)

Notes:

• Security Council has 15 members (5 permanent + 10 rotating)
• Before 1965: 11 members (5 permanent + 6 rotating)
• Any P5 member voting "N" = VETO (resolution fails)

P5 Members (Permanent with Veto Power):

• CHN (China)
• FRA (France)
• GBR (United Kingdom)
• RUS (Russian Federation / USSR before 1991)
• USA (United States)

Country Code Examples:

• P5: CHN (China), FRA (France), GBR (UK), RUS/SUN (Russia/USSR), USA (United States)
• Non-permanent (examples): JPN (Japan), BRA (Brazil), IND (India), etc.

For detailed voting analysis, see: VOTING_REFERENCE.md

---

13. GEOGRAPHIC (6 fields) - FROM FILE 1

Geographic/country metadata. These appear to be for countries that are subjects of resolutions, not voters.

"geographic": {
  "iso_alpha3": "SSD",                    // ISO 3-letter code
  "iso_name": "South Sudan",              // Country name
  "m49_countrycode": "728",               // UN M49 code
  "m49_region": "002",                    // UN region code (Africa=002)
  "m49_region_sub": "014",                // Sub-region (Eastern Africa=014)
  "m49_region_intermediate": null         // Intermediate region
}

Source: File 1 (columns: iso_alpha3, iso_name, m49_countrycode, m49_region, m49_region_sub, m49_region_intermediate) Coverage: Partial (not all resolutions concern specific countries)

---

14. URLS - RESOLUTIONS (6 fields) - FROM FILE 1

Direct links to resolution documents in all 6 UN languages.

"urls_resolution": {
  "en": "https://undocs.org/en/S/RES/2758(2024)",
  "ar": "https://undocs.org/ar/S/RES/2758(2024)",
  "es": "https://undocs.org/es/S/RES/2758(2024)",
  "fr": "https://undocs.org/fr/S/RES/2758(2024)",
  "ru": "https://undocs.org/ru/S/RES/2758(2024)",
  "zh": "https://undocs.org/zh/S/RES/2758(2024)"
}

Source: File 1 (columns: url_res_en, url_res_ar, url_res_es, url_res_fr, url_res_ru, url_res_zh) Coverage: 100%

---

15. URLS - DRAFTS (6 fields) - FROM FILE 1

Direct links to draft resolution documents in all 6 UN languages.

"urls_draft": {
  "en": "https://undocs.org/en/S/2024/12",
  "ar": "https://undocs.org/ar/S/2024/12",
  "es": "https://undocs.org/es/S/2024/12",
  "fr": "https://undocs.org/fr/S/2024/12",
  "ru": "https://undocs.org/ru/S/2024/12",
  "zh": "https://undocs.org/zh/S/2024/12"
}

Source: File 1 (columns: url_draft_en, url_draft_ar, url_draft_es, url_draft_fr, url_draft_ru, url_draft_zh) Coverage: ~96%

---

16. URLS - MEETINGS (6 fields) - FROM FILE 1

Direct links to meeting records in all 6 UN languages.

"urls_meeting": {
  "en": "https://undocs.org/en/S/PV.9521",
  "ar": "https://undocs.org/ar/S/PV.9521",
  "es": "https://undocs.org/es/S/PV.9521",
  "fr": "https://undocs.org/fr/S/PV.9521",
  "ru": "https://undocs.org/ru/S/PV.9521",
  "zh": "https://undocs.org/zh/S/PV.9521"
}

Source: File 1 (columns: url_meeting_en, url_meeting_ar, url_meeting_es, url_meeting_fr, url_meeting_ru, url_meeting_zh) Coverage: ~100%

---

17. URLS - RECORDS (3 fields) - FROM FILE 1

Links to main record pages.

"urls_records": {
  "main": "https://digitallibrary.un.org/record/...",
  "draft": "https://digitallibrary.un.org/record/...",
  "meeting": "https://digitallibrary.un.org/record/..."
}

Source: File 1 (columns: url_record, url_record_draft, url_record_meeting) Coverage: ~100%

---

18. ADMINISTRATIVE (8 fields) - FROM FILE 1

Administrative metadata and provenance.

"administrative": {
  "series": "S/RES",                              // Document series
  "doi_concept": "10.18356/...",                  // DOI identifier
  "doi_version": "10.18356/.../v1",               // DOI version
  "license": "CC BY 3.0 IGO",                     // License
  "version": "1.0",                               // Record version
  "related_resource": "Related documents...",     // Related resources
  "committee_report": "Committee reports...",     // Committee reports
  "contains": "Document contains..."              // Contents description
}

Source: File 1 (columns: series, doi_concept, doi_version, license, version, related_resource, committee_report, contains) Coverage: Varies by field

---

🔄 Data Transformations Applied

1. Symbol Normalization (November 9, 2024)

Problem: Symbol formatting mismatch between files

• File 1: S/RES/2065 (2012) ← space before year
• File 2: S/RES/2065(2012) ← no space

Solution: Applied regex normalization to remove spaces before parentheses

Impact:

• Member state vote coverage: 75.8% → 100% ✅
• Fixed 658 missing matches
• See: MERGE_FIX_NOTES.md

2. Draft Symbol Field Addition (November 9, 2024)

Problem: Draft symbol from File 1 was not transferred to unified dataset

Solution: Added draft_symbol field to draft_from_file1 section

Impact:

• Draft symbol coverage: 62.9% → 97.7% ✅
• Improved by 34.8 percentage points

3. Vote Type Simplification (November 9, 2024)

Problem: Source data had 4 vote types (Y/N/A/X) with unclear distinction

Solution: Merged "X" (Not Participating) into "A" (Abstain)

Impact:

• Vote types: 4 → 3 (Y/N/A) ✅
• Simplified analysis
• 1,258 X votes converted to A (170 resolutions affected)
• See: CONVERSION_X_TO_A_NOTES.md

4. 2024 Year Completion (November 9, 2024)

Problem: File 1 only had 1 resolution from 2024 (S/RES/2722 from Jan 10)

Solution: Added 45 missing 2024 resolutions (S/RES/2723 through S/RES/2767) using Files 2 & 3

Impact:

• Total resolutions: 2,722 → 2,767 ✅
• Complete 2024 coverage through December 27
• All 2024 resolutions have: member votes (100%), draft PDF text (100%)
• Missing for Feb-Dec 2024: full resolution text, thematic coding (File 1 only)

---

📊 Data Provenance Summary

FROM FILE 1 (Base - 2,722 resolutions)

Provides: Core metadata, full text, thematic coding, URLs, draft text

✅ Always Present (100%):

• Identifiers (symbol, res_no, year, etc.)
• Dates (date, vote_date)
• Meeting info (meeting_record, meeting_no)
• Content (title, summary, topic, subjects)
• Resolution text (English)
• Voting totals (aggregate numbers)
• URLs (all 21 URL fields)

✅ Usually Present (96-100%):

• Multilingual text (99.9%)
• Draft symbol (97.7%)
• Draft text (96.4%)

✅ Partially Present (34%):

• Thematic coding (34.2% tagged)
• Geographic metadata (when relevant)

---

FROM FILE 2 (Enrichment - 40,929 individual votes)

Provides: Individual member state voting records

✅ Coverage: 100% (2,722/2,722 resolutions)

Unique Contribution:

• Member state codes (ms_code)
• Member state names (ms_name)
• Individual votes (Y/N/A)
• Permanent member flags

Why 100%?:

• Symbol normalization fix resolved all matching issues
• All resolutions now have individual country votes

---

FROM FILE 3 (Enrichment - 1,712 draft PDFs)

Provides: Extracted draft resolution PDF text

✅ Coverage: 62.9% (1,712/2,722 resolutions)

Unique Contribution:

• Draft PDF text (from extracted PDFs)
• Draft metadata (page count, char count, filename)
• Only includes successful extractions (no errors)

Why Not Higher?:

• Not all resolutions have draft PDFs available
• Some PDFs couldn't be extracted
• File 1 already provides most draft text (96.4%)

Value Add:

• Provides 1,712 drafts with clean PDF extraction
• 1,029 resolutions have drafts from BOTH sources (cross-validation)

---

📅 Timeline Distribution

Resolutions by decade:

Decade	Count	Percentage
1940s	78	2.9%
1950s	54	2.0%
1960s	143	5.3%
1970s	186	6.8%
1980s	185	6.8%
1990s	638	23.4%
2000s	623	22.9%
2010s	596	21.9%
2020s	219	8.0%

Notes:

• Significant increase starting in 1990s (post-Cold War)
• Steady high volume in 1990s-2010s
• 2020s incomplete (only through 2024)

---

💻 Usage Examples

1. Loading the Data

Python (pandas):

import pandas as pd

# Load entire dataset
df = pd.read_json('unified_unsc_resolutions.jsonl', lines=True)

# Access basic fields
print(df[['identifiers', 'dates', 'content']].head())

# Get resolution symbols
df['symbol'] = df['identifiers'].apply(lambda x: x['symbol'])
df['year'] = df['identifiers'].apply(lambda x: x['year'])

Python (raw JSON):

import json

with open('unified_unsc_resolutions.jsonl', 'r') as f:
    for line in f:
        resolution = json.loads(line)
        print(resolution['identifiers']['symbol'])

JavaScript/Node.js:

const fs = require('fs');
const readline = require('readline');

const rl = readline.createInterface({
    input: fs.createReadStream('unified_unsc_resolutions.jsonl')
});

rl.on('line', (line) => {
    const resolution = JSON.parse(line);
    console.log(resolution.identifiers.symbol);
});

---

2. Common Queries

Find all Chapter VII resolutions:

chapter7 = df[df['thematic_coding'].apply(lambda x: x.get('chapter7') == True)]
print(f"Chapter VII resolutions: {len(chapter7)}")

Get resolutions with individual votes:

with_votes = df[df['member_state_votes'].apply(lambda x: x is not None and len(x) > 0)]
print(f"Resolutions with member votes: {len(with_votes)}")
# Result: 2,722 (100%)

Find China's votes on Middle East resolutions:

def get_china_vote(row):
    votes = row.get('member_state_votes', [])
    if votes:
        for v in votes:
            if v['code'] == 'CHN':
                return v['vote']
    return None

df['china_vote'] = df.apply(get_china_vote, axis=1)
middle_east = df[df['content'].apply(lambda x: 'Middle East' in str(x.get('title', '')))]
china_middle_east = middle_east[middle_east['china_vote'].notna()]
print(china_middle_east[['symbol', 'china_vote', 'content']])

Analyze P5 veto patterns:

def check_veto(row):
    """Check if any P5 member voted NO (veto)"""
    votes = row.get('member_state_votes', [])
    for v in votes:
        if v.get('permanent_member') and v.get('vote') == 'N':
            return v['name']
    return None

df['vetoed_by'] = df.apply(check_veto, axis=1)
vetoes = df[df['vetoed_by'].notna()]
print(f"Resolutions with P5 veto: {len(vetoes)}")
# Note: Most vetoes prevent adoption, check sc_vetoed_drafts.jsonl for failed drafts

Get resolutions about South Sudan:

south_sudan = df[df['content'].apply(
    lambda x: 'South Sudan' in str(x.get('subjects', '')) or
              'South Sudan' in str(x.get('title', ''))
)]
print(f"South Sudan resolutions: {len(south_sudan)}")

Compare draft text sources:

has_file1_draft = df['draft_from_file1'].apply(
    lambda x: x.get('text_draft') is not None and len(str(x.get('text_draft', ''))) > 10
)
has_file3_draft = df['draft_pdf'].apply(
    lambda x: x is not None and x.get('draft_text') is not None
)

print(f"Drafts from File 1: {has_file1_draft.sum()}")
print(f"Drafts from File 3: {has_file3_draft.sum()}")
print(f"Both sources: {(has_file1_draft & has_file3_draft).sum()}")

---

3. Export Subsets

Export only essential fields (reduced size):

import json

essential = []

with open('unified_unsc_resolutions.jsonl', 'r') as f:
    for line in f:
        record = json.loads(line)

        # Create compact version
        compact = {
            'symbol': record['identifiers']['symbol'],
            'date': record['dates']['date'],
            'title': record['content']['title'],
            'text': record['resolution_text']['text_en'],
            'chapter7': record['thematic_coding'].get('chapter7'),
            'votes': record['member_state_votes'],
            'url': record['urls_resolution']['en']
        }
        essential.append(compact)

# Write compact version
with open('compact_unsc.jsonl', 'w') as f:
    for rec in essential:
        f.write(json.dumps(rec) + '\n')

Export to CSV (flattened):

import pandas as pd
import json

records = []
with open('unified_unsc_resolutions.jsonl', 'r') as f:
    for line in f:
        rec = json.loads(line)
        flat = {
            'symbol': rec['identifiers']['symbol'],
            'year': rec['identifiers']['year'],
            'date': rec['dates']['date'],
            'title': rec['content']['title'],
            'chapter7': rec['thematic_coding'].get('chapter7'),
            'vote_yes': rec['voting_totals'].get('vote_yes'),
            'vote_no': rec['voting_totals'].get('vote_no'),
            'has_member_votes': len(rec.get('member_state_votes', [])) > 0,
            'has_draft': rec.get('draft_pdf') is not None
        }
        records.append(flat)

df = pd.DataFrame(records)
df.to_csv('unsc_resolutions_flat.csv', index=False)

---

✅ Data Quality Notes

Completeness by Field Category:

Category	Coverage	Source
Basic metadata	100%	File 1
Resolution text (English)	100%	File 1
Multilingual text	99.9%	File 1
URLs	100%	File 1
Voting totals	100%	File 1
Member state votes	100%	File 2
Draft symbol	97.7%	File 1
Draft text (either source)	97.3%	Files 1+3
Thematic coding	34.2%	File 1
Geographic metadata	Partial	File 1

Known Characteristics:

1. Thematic coding (65.8% untagged):

   • Many resolutions are procedural and correctly not tagged
   • Newer resolutions more likely to be coded
   • Selective tagging for significant resolutions

2. Draft text from File 3 (37.1% missing):

   • Not all drafts available as PDFs
   • Some PDFs couldn't be extracted
   • File 1 covers most gaps (96.4% coverage)

3. Geographic metadata (partial):

   • Only populated for resolutions concerning specific countries
   • Many resolutions are procedural/global and don't have geographic tags

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📦 File Size Optimization

Current Size: 514 MB

Breakdown:

• Multilingual text (5 languages): ~350 MB
• English text + metadata: ~100 MB
• Member votes + drafts: ~50 MB
• URLs + admin: ~14 MB

To Reduce Size:

Option 1: Remove multilingual text (~100 MB result)

Remove fields: resolution_text_multilingual

Option 2: Remove all text (~30 MB result)

Keep only metadata, votes, URLs. Remove:

• resolution_text
• resolution_text_multilingual
• draft_from_file1
• draft_pdf
• meeting_text

Option 3: Compress with gzip (~50-80 MB result)

gzip unified_unsc_resolutions.jsonl
# Creates: unified_unsc_resolutions.jsonl.gz (~80 MB)

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📚 Related Documentation

• VOTING_REFERENCE.md - Complete voting analysis guide
• QUICK_REFERENCE.md - Quick lookup guide
• DATA_FLOW_SUMMARY.md - Data integration flow with diagrams
• MERGE_FIX_NOTES.md - Symbol normalization fix details
• CONVERSION_X_TO_A_NOTES.md - Vote type conversion details

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🛠️ Source Files

Input Files:

1. CR-UNSC_2024-05-19_ALL_CSV_FULL.csv

   • 2,722 resolutions, 82 columns, 347.4 MB
   • Full text, metadata, thematic coding, URLs

2. 2025_7_21_sc_voting.csv

   • 40,929 individual votes, 20 columns, 14.2 MB
   • One row per member state vote

3. sc_voting_with_drafts_final.jsonl

   • 2,787 records with nested voting data
   • Extracted draft PDF text

Processing:

• Merge Script: merge_unsc_data.py
• Conversion Script: convert_x_to_a.py

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📖 Recommended Citation

If using this dataset, please cite the original sources:

File 1 (CR-UNSC):

• UN Security Council Resolutions Corpus
• Coverage: 1946-2024
• Source: UN Digital Library

File 2 (Voting Records):

• UN Security Council Voting Data
• Coverage: 1946-2025
• Individual member state votes

File 3 (Draft PDFs):

• Extracted draft resolution texts
• Coverage: Selected resolutions with available PDFs

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📝 Version History

v1.1 (November 9, 2024) - Current

• ✅ Added complete 2024 coverage (45 new resolutions)
• ✅ Extended to 2,767 total resolutions (1946-2024)
• ✅ All 2024 resolutions through December 27, 2024
• ✅ S/RES/2722 to S/RES/2767 (46 resolutions from 2024)

v1.0 (November 9, 2024)

• ✅ Initial unified dataset
• ✅ Combined Files 1, 2, and 3
• ✅ 2,722 resolutions (1946-2024 Jan)
• ✅ Full metadata, voting, and draft text
• ✅ Applied symbol normalization (100% vote coverage)
• ✅ Added draft symbol field (97.7% coverage)
• ✅ Simplified vote types to Y/N/A

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📞 Contact & Support

For questions about this dataset structure, please refer to:

• Documentation: This file and related .md files
• Source Files: See "Source Files" section above
• Merge Script: merge_unsc_data.py

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📎 Appendix: Quick Field Lookup

Field Path	Description	Source	Type
identifiers.symbol	Resolution symbol (S/RES/XXX)	File 1	string
identifiers.year	Year of resolution	File 1	integer
dates.date	Adoption date	File 1	string (ISO date)
content.title	Official title	File 1	string
thematic_coding.chapter7	Chapter VII flag	File 1	boolean
resolution_text.text_en	English text	File 1	string
draft_from_file1.draft_symbol	Draft symbol	File 1	string
voting_totals.vote_yes	Total yes votes	File 1	integer
member_state_votes	Individual votes	File 2	array
member_state_votes[].vote	Vote value (Y/N/A)	File 2	string
draft_pdf.draft_text	Draft PDF text	File 3	string
urls_resolution.en	English URL	File 1	string

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Last Updated: November 9, 2024 Format Version: 1.1 Total Records: 2,767 (complete through December 2024) Status: ✅ Production Ready