Medieval Universitates Queries 20250914

Generated: October 23, 2025 at 04:55 AM

Chapter 1 Computational Analysis

Strategic Database Queries: Medieval Universitates and Digital Commons

Generated: September 14, 2025

Based on the theoretical frameworks in master_document.md, these queries surface evidence of collective study practices, tactical knowledge-sharing (de Certeau), and medieval universitates parallels in CUNY Reddit communities.

---

Line of Inquiry 1: Registration Tactics and CUNYfirst Workarounds

Research Question: How do students deploy de Certeau’s “tactics” to navigate institutional registration systems, creating collective knowledge about temporal “cracks” in surveillance?

Theoretical Connection: De Certeau’s tactics as “clever utilization of time” - students exploiting millisecond gaps in registration systems, sharing provisional knowledge that must be re-validated each semester.

Query 1.1: Registration Workarounds and Shopping Cart Tricks

-- Find evidence of tactical registration knowledge-sharing
SELECT 
    'submission_' || REPLACE(s.id, 't3_', '') as evidence_id,
    s.title,
    s.selftext,
    s.author,
    datetime(s.created_utc, 'unixepoch') as posted_date,
    s.score,
    s.num_comments,
    s.subreddit
FROM submissions s
WHERE (
    -- Registration tactics
    LOWER(s.title || ' ' || s.selftext) LIKE '%shopping cart%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%registration trick%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%cunyfirst hack%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%drop and re-enroll%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%waitlist trick%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%override%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%closed class%'
    OR (LOWER(s.title || ' ' || s.selftext) LIKE '%registration%' 
        AND LOWER(s.title || ' ' || s.selftext) LIKE '%tip%')
)
ORDER BY s.score DESC, s.num_comments DESC
LIMIT 50;

Query 1.2: Temporal Patterns of Registration Support

-- Analyze when registration help peaks (24/7 peer support vs 9-5 institutional)
SELECT 
    CAST(strftime('%H', datetime(created_utc, 'unixepoch', 'localtime')) AS INTEGER) as hour_of_day,
    COUNT(*) as post_count,
    AVG(score) as avg_score,
    SUM(num_comments) as total_engagement
FROM (
    SELECT * FROM submissions 
    WHERE LOWER(title || ' ' || selftext) LIKE '%registration%'
       OR LOWER(title || ' ' || selftext) LIKE '%cunyfirst%'
       OR LOWER(title || ' ' || selftext) LIKE '%enroll%'
    UNION ALL
    SELECT s.* FROM submissions s
    JOIN comments c ON s.id = c.submission_id
    WHERE LOWER(c.body) LIKE '%registration%'
       OR LOWER(c.body) LIKE '%cunyfirst%'
)
GROUP BY hour_of_day
ORDER BY hour_of_day;

Query 1.3: Cross-Campus Knowledge Networks

-- Evidence of inter-campus tactical knowledge sharing
ATTACH DATABASE '/Users/zacharymuhlbauer/Desktop/studio/projects/reddit-diss/databases/current/Baruch_historical_data.db' AS baruch;
ATTACH DATABASE '/Users/zacharymuhlbauer/Desktop/studio/projects/reddit-diss/databases/current/HunterCollege_historical_data.db' AS hunter;

SELECT 
    'comment_' || REPLACE(c.id, 't1_', '') as evidence_id,
    c.author,
    c.body,
    datetime(c.created_utc, 'unixepoch') as posted_date,
    'CUNY' as source_db,
    c.score
FROM main.comments c
WHERE c.body LIKE '%Baruch%' AND c.body LIKE '%trick%'
   OR c.body LIKE '%Hunter%' AND c.body LIKE '%registration%'
   OR c.body LIKE '%Queens%' AND c.body LIKE '%cunyfirst%'
UNION ALL
SELECT 
    'comment_' || REPLACE(c.id, 't1_', '') as evidence_id,
    c.author,
    c.body,
    datetime(c.created_utc, 'unixepoch') as posted_date,
    'Baruch' as source_db,
    c.score
FROM baruch.comments c
WHERE c.body LIKE '%CUNY%' OR c.body LIKE '%Hunter%' OR c.body LIKE '%Queens%'
LIMIT 100;

---

Line of Inquiry 2: Collective Study and Resource Redistribution

Research Question: How do students create “poles of attention” (Giroux) through resource sharing that redistributes educational materials outside market mechanisms?

Theoretical Connection: Medieval universitates’ collective bargaining power transformed into digital mutual aid networks; bell hooks’ “education as practice of freedom.”

Query 2.1: Textbook and Study Material Sharing Networks

-- Document resource redistribution practices
SELECT 
    'submission_' || REPLACE(s.id, 't3_', '') as evidence_id,
    s.title,
    s.selftext,
    s.author,
    datetime(s.created_utc, 'unixepoch') as posted_date,
    s.score,
    s.num_comments,
    s.subreddit
FROM submissions s
WHERE (
    -- Textbook sharing
    LOWER(s.title || ' ' || s.selftext) LIKE '%textbook%pdf%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%free textbook%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%libgen%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%study guide%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%notes%share%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%study group%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%discord%study%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%groupme%'
)
AND s.score > 5  -- Community validated
ORDER BY s.score DESC, s.num_comments DESC
LIMIT 50;

Query 2.2: Mutual Aid and Food Resource Networks

-- Evidence of basic needs support networks
SELECT 
    'submission_' || REPLACE(s.id, 't3_', '') as evidence_id,
    s.title,
    s.selftext,
    s.author,
    datetime(s.created_utc, 'unixepoch') as posted_date,
    s.score,
    s.num_comments,
    CASE 
        WHEN LOWER(s.title || ' ' || s.selftext) LIKE '%food%pantr%' THEN 'food_pantry'
        WHEN LOWER(s.title || ' ' || s.selftext) LIKE '%housing%' THEN 'housing'
        WHEN LOWER(s.title || ' ' || s.selftext) LIKE '%metrocard%' THEN 'transportation'
        WHEN LOWER(s.title || ' ' || s.selftext) LIKE '%emergency%' THEN 'emergency_aid'
        ELSE 'mutual_aid'
    END as aid_type
FROM submissions s
WHERE (
    LOWER(s.title || ' ' || s.selftext) LIKE '%food pantr%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%mutual aid%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%emergency fund%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%housing insecur%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%can''t afford%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%financial help%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%metrocard%'
    OR LOWER(s.title || ' ' || s.selftext) LIKE '%CARES%'
)
ORDER BY s.created_utc DESC
LIMIT 100;

Query 2.3: Collective Validation Through Upvoting (Medieval Disputations)

-- Analyze knowledge validation patterns through community voting
WITH high_value_threads AS (
    SELECT 
        s.id,
        s.title,
        s.score,
        s.num_comments,
        s.score / NULLIF(s.num_comments, 0) as engagement_ratio,
        COUNT(DISTINCT c.author) as unique_participants
    FROM submissions s
    LEFT JOIN comments c ON s.id = c.submission_id
    WHERE s.score > 20  -- Community validated
    GROUP BY s.id
    HAVING unique_participants > 5  -- Collective engagement
)
SELECT 
    'submission_' || REPLACE(id, 't3_', '') as evidence_id,
    title,
    score as community_validation_score,
    num_comments,
    unique_participants,
    ROUND(engagement_ratio, 2) as validation_intensity,
    CASE
        WHEN title LIKE '%professor%' OR title LIKE '%class%' THEN 'academic_knowledge'
        WHEN title LIKE '%registration%' OR title LIKE '%cunyfirst%' THEN 'bureaucratic_navigation'
        WHEN title LIKE '%study%' OR title LIKE '%exam%' THEN 'collective_study'
        WHEN title LIKE '%help%' OR title LIKE '%need%' THEN 'mutual_support'
        ELSE 'general_knowledge'
    END as knowledge_type
FROM high_value_threads
ORDER BY score DESC
LIMIT 50;

---

Line of Inquiry 3: Temporal Crisis Support Networks

Research Question: How do 24/7 peer support networks compensate for institutional 9-5 limitations, creating what Simon calls “witness as collective study”?

Theoretical Connection: Roger Simon’s “remembrance-learning” where communities develop ethical responses through collective witnessing; Stengers’ “ecology of practices.”

Query 3.1: Late-Night Support Networks (2-3am Peak Activity)

-- Document after-hours peer support when institutions are closed
SELECT 
    strftime('%H', datetime(created_utc, 'unixepoch', 'localtime')) as hour,
    COUNT(*) as posts,
    AVG(score) as avg_engagement,
    GROUP_CONCAT(DISTINCT 
        CASE 
            WHEN body LIKE '%depress%' OR body LIKE '%anxiety%' THEN 'mental_health'
            WHEN body LIKE '%homeless%' OR body LIKE '%evict%' THEN 'housing_crisis'
            WHEN body LIKE '%hungry%' OR body LIKE '%food%' THEN 'food_insecurity'
            WHEN body LIKE '%registration%' OR body LIKE '%deadline%' THEN 'academic_emergency'
            WHEN body LIKE '%financial aid%' OR body LIKE '%tuition%' THEN 'financial_crisis'
            ELSE NULL
        END
    ) as crisis_types
FROM comments
WHERE created_utc IS NOT NULL
    AND (body LIKE '%help%' OR body LIKE '%emergency%' OR body LIKE '%urgent%' OR body LIKE '%crisis%')
GROUP BY hour
HAVING CAST(hour AS INTEGER) NOT BETWEEN 9 AND 17  -- Outside business hours
ORDER BY CAST(hour AS INTEGER);

Query 3.2: Collective Witnessing of Institutional Failure

-- Simon's "witness as collective study" - documenting systematic issues
SELECT 
    'submission_' || REPLACE(s.id, 't3_', '') as evidence_id,
    s.title,
    s.selftext,
    s.author,
    datetime(s.created_utc, 'unixepoch') as posted_date,
    s.score,
    s.num_comments,
    COUNT(DISTINCT c.author) as witnesses,
    SUM(CASE WHEN c.body LIKE '%same%' OR c.body LIKE '%me too%' OR c.body LIKE '%also%' THEN 1 ELSE 0 END) as solidarity_responses
FROM submissions s
JOIN comments c ON s.id = c.submission_id
WHERE (
    -- Institutional failures
    s.selftext LIKE '%advisor%never%'
    OR s.selftext LIKE '%office%closed%'
    OR s.selftext LIKE '%no response%'
    OR s.selftext LIKE '%system%down%'
    OR s.selftext LIKE '%can''t reach%'
    OR s.selftext LIKE '%budget cut%'
    OR s.selftext LIKE '%laid off%'
    OR s.selftext LIKE '%library%closed%'
)
GROUP BY s.id
HAVING witnesses > 3  -- Collective witnessing
ORDER BY witnesses DESC, s.score DESC
LIMIT 50;

Query 3.3: Cross-Campus Solidarity During Crisis

-- Evidence of inter-campus support networks during emergencies
WITH crisis_threads AS (
    SELECT 
        s.id,
        s.title,
        s.selftext,
        s.author,
        s.created_utc,
        s.subreddit,
        'submission' as content_type
    FROM submissions s
    WHERE datetime(s.created_utc, 'unixepoch') >= '2020-03-01'
        AND datetime(s.created_utc, 'unixepoch') <= '2020-05-31'
        AND (s.selftext LIKE '%pandemic%' OR s.selftext LIKE '%covid%' OR s.selftext LIKE '%emergency%')
)
SELECT 
    'submission_' || REPLACE(ct.id, 't3_', '') as evidence_id,
    ct.title,
    ct.author as original_poster,
    ct.subreddit as origin_campus,
    COUNT(DISTINCT c.author) as responders,
    COUNT(DISTINCT 
        CASE 
            WHEN c.body LIKE '%Baruch%' THEN 'Baruch'
            WHEN c.body LIKE '%Hunter%' THEN 'Hunter'
            WHEN c.body LIKE '%Queens%' THEN 'Queens'
            WHEN c.body LIKE '%CCNY%' THEN 'CCNY'
            WHEN c.body LIKE '%Brooklyn%' THEN 'Brooklyn'
            ELSE NULL
        END
    ) as campuses_mentioned,
    datetime(ct.created_utc, 'unixepoch') as crisis_date
FROM crisis_threads ct
JOIN comments c ON ct.id = c.submission_id
GROUP BY ct.id
HAVING campuses_mentioned > 1  -- Cross-campus dialogue
ORDER BY responders DESC
LIMIT 30;

---

Execution Strategy

1. Run Registration Tactics Queries

# Execute across all CUNY databases
for db in CUNY Baruch HunterCollege QueensCollege CCNY BrooklynCollege CUNYuncensored JohnJay; do
    echo "=== Analyzing $db ==="
    sqlite3 databases/current/${db}_historical_data.db < query_1_1.sql > results/${db}_registration_tactics.txt
done

2. Analyze Temporal Patterns

# Combine temporal data from all campuses
sqlite3 databases/current/CUNY_historical_data.db < query_1_2.sql > temporal_registration_support.csv
python3 analyze_temporal_patterns.py temporal_registration_support.csv

3. Document Collective Study Networks

# Map resource sharing networks
sqlite3 databases/current/CUNY_historical_data.db < query_2_1.sql > textbook_sharing_network.txt
sqlite3 databases/current/CUNY_historical_data.db < query_2_2.sql > mutual_aid_network.txt

---

Expected Patterns & Evidence

De Certeau’s Tactics

• Shopping cart workarounds documented with step-by-step instructions
• Temporal exploitation patterns (millisecond gaps, midnight registration)
• Provisional knowledge marked with uncertainty (“I think”, “might work”)
• Re-validation cycles each semester

Medieval Universitates Parallels

• Upvoting as modern disputations (collective knowledge validation)
• Cross-campus networks resembling medieval “nations”
• Threat of collective action (boycotts, protests) as leverage
• Self-governance through community moderation

Collective Intelligence (Lévy)

• Distributed problem-solving across multiple threads
• Knowledge accumulation in searchable archives
• “None of us knows everything” explicitly stated
• Complementary expertise (business + nursing + engineering)

Crisis Support Networks

• Peak activity 2-3am when offices closed
• Immediate peer response vs days waiting for advisors
• Solidarity responses validating shared experiences
• Emergency resource redistribution outside institutional channels

---

Connection to September 14 Entry Themes

1. Medieval University Structure: Queries surface evidence of self-governing educational spaces with democratic knowledge validation through upvoting

2. Registration Workarounds: Specific “Baruch shopping cart trick” and similar tactics documented with community validation scores

3. Collective Study: Textbook PDF sharing, study group organization, and resource redistribution networks clearly mapped

4. Temporal Patterns: 24/7 peer support documented with hourly breakdowns showing after-hours crisis response

5. Cross-Campus Networks: Inter-campus knowledge sharing and solidarity networks during emergencies

These queries will provide quantitative evidence supporting the theoretical frameworks while preserving specific evidence IDs for academic citation in the dissertation narrative.

Evidence References (1 items) ▶

Submissions (1)

• submission_id