courses:activists:module-01
Table of Contents
Module 01 — Campaign-scale RTI design
When one RTI isn't enough
Single RTI = one data point. Multi-RTI campaigns = pattern. To prove systemic problems (not isolated incidents), you need: same questions, same period, scaled across geographies / departments / years.
Examples:
- 'PMAY housing allotment irregularities' — needs 50+ district RTIs
- 'Mid-day meal scheme leakage' — needs 100+ school + 30+ DEO RTIs
- 'CAG audit follow-up' — needs ministry + state-cell RTIs
The 4-axis grid
Design every campaign on 4 axes:
- Geographic axis: districts/states (X RTIs)
- Time axis: years (FY 2020-21 to 2025-26 = 6 years)
- Department axis: cross-cutting (revenue + welfare + audit)
- Question axis: identical sub-questions across all RTIs (so responses can be tabulated)
A tight 4-axis grid produces a publication-ready dataset on receipt.
Identical-question rigor
For tabulation to work, every RTI must have literally identical sub-questions:
- (a) Number of beneficiaries enrolled in [scheme] in FY [year], your district.
- (b) Number of beneficiaries who received the FIRST instalment.
- © Number who received the SECOND.
- (d) Total funds disbursed (₹ lakh).
- (e) Number of complaints received about non-disbursal.
- (f) Number of complaints resolved.
If any RTI varies the question, that data point drops out of the analysis.
Volunteer-scale logistics
For a 100+ RTI campaign:
- Use a central spreadsheet with columns: state, district, PIO, ref no., filing date, response status, response excerpt.
- Recruit state coordinators to file from local addresses (some states require local addresses).
- Pre-stamp + pre-address envelopes at one central location, then ship to volunteers.
- Consolidated First Appeal pack ready when ~30% of RTIs return refusals.
Pattern recognition
Once 60-70% of RTIs return:
- Compare similar districts for variance — large variance = local irregularity worth investigating.
- Compare year-on-year within a district — sudden change = signal.
- Compute disclosure rate by state/department — low disclosure rate = system opacity (a story in itself).
- Identify outliers: 1-2 PIOs who give exemplary responses (use as 'compliance benchmark' in your report).
✅ Quiz
Quiz available from your course dashboard.
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Last reviewed: 24 April 2026.
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courses/activists/module-01.txt · Last modified: by 127.0.0.1

