New Delhi: The Election Commission of India or ECI has released the numbers of electors who have been flagged for potential deletion from the voter rolls – approximately 65 lakh people – representing an average disenfranchisement risk (ADR) of 8.3% across the state. 

According to the data, 15 of the 38 districts in Bihar have higher rates of disenfranchisement risk than the state’s average. These are: Gopalgunj, Purnia, Kishanganj, Madhubani, Bhagalpur, Saharsa, Madhepura, Sitamarhi, Sheohar, Samastipur, Saran, Bhojpur, Purvi Champaran, Siwan and Vaishali. This analysis is based on district-level data as the constituency-level data is still awaited.

Actual ECI data now has Gopalganj with 15.1% fearing disenfranchisement, Purnia with 12.07% at number two, and Kishanganj with 11.82%. These districts, with risks far in excess of the state average, reveal the systematic nature of the political threat. The process targets the opposition's core voters whether they form the ruling majority (as in the Mahagathbandhan stronghold of Kishanganj) or the opposition minority (as within the NDA strongholds of Gopalganj and Purnia).

These are crucial battleground districts and the smallest of vote differentials may be likely to effect big electoral shifts. The Assembly elections in 2020, where the Rashtriya Janata Dal (RJD) emerged as the single largest party in the state, saw a significant number of victories settled by slender margins.

Our analysis, listing districts in sequence of the disenfranchisement risk they face, also confirms that Saran (#11 risk), Bhojpur (#12 risk), and Siwan (#14 risk) – which are Mahagathbandhan (MGB) bastions – are now confirmed as zones with a high-risk of voter disenfranchisement. This directly threatens the core political support base of the RJD. The same goes for the MGB's urban stronghold of Patna (#19 risk, 9 MGB seats) and its bastions in the Magadh region like Aurangabad (#16 risk, 8.30% ADR), which the opposition alliance swept in 2020.

The state's key battlegrounds – Samastipur (#10 risk), Vaishali (#15), and Muzaffarpur (#18) – all rank above the state average of disenfranchisement, that is with a risk rate above 8%. With electoral victories in assembly polls having been secured with the help of small margins, disenfranchising a small percentage of an opponent's core votes is enough to flip several constituencies. For example, in Madhepura (#8 risk, 9.32% ADR), where NDA and MGB got two seats each, a high risk of disenfranchisement can switch fortunes dramatically. 

On perusing the data, we have also found three distinct centres of ‘risk’. The Migration belt (Gopalganj, Saran, Siwan), threatening the RJD's core heartland, as well as Urban centres (Bhagalpur, Patna), threatening the urban poor and the Dalit vote. Disenfranchisement in the Seemanchal-Mithilanchal arc (Purnia, Kishanganj, Madhubani) threatens the consolidated minority vote crucial for the MGB and AIMIM.

There has been a persistent fear that opposition political parties have expressed ever since the Special Intensive Revision or SIR was launched by the ECI on June 25. They have maintained that their voters, amongst the most marginalised and backward were least likely to possess documents the ECI has been insisting on. 

In its last hearing on the matter, the Supreme Court had assured petitioners it would step in if there were 'mass deletions.' Our analysis of the ECI's own data confirms that the potential deletions are intensely concentrated in specific geographic belts that are critical to the opposition.

In the first part of this analysis, when The Wire drew up a Vulnerability Index, we argued that a new Election Commission (EC) directive for revising voter rolls in Bihar posed a clear and present danger to the state’s most vulnerable citizens. By creating a Vulnerability Index, we identified the districts where the intersection of poverty, educational deprivation and minority status would likely lead to mass disenfranchisement.

Now, the first phase of the EC's Summary Intensive Revision (SIR) exercise is complete. The data is in. 

We can now compare our initial vulnerability assessment with the final ECI data to reveal the real-world impact of the directive. By cross-referencing this disenfranchisement risk with the granular results of the 2020 assembly election, we can map the political consequences of this administrative exercise.

Ground truth: Predicted vulnerability vs. Actual risk

To begin, we ranked all 38 districts according to their Actual Disenfranchisement Risk (ADR) – the final percentage of flagged electors as per the EC's data. This ranking represents the real-world impact, district by district.

The following master table is the centerpiece of our analysis. 

It juxtaposes our predicted Vulnerability Index Rank with the actual, data-driven ADR rank, confirming the accuracy of our initial model and more importantly, the administrative blind spots it did not foresee.

Master Analysis Table: Predicted Vulnerability vs. Ground Reality

Five key findings from the data

The master table reveals a story of both confirmed fears and new, alarming trends. Five exhaustive takeaways emerge.

1. The tiers of electoral risk
   The districts fall into three clear tiers of vulnerability:

• Tier 1: Critical risk (ADR > 10%): Gopalganj, Purnia, Kishanganj, Madhubani, Bhagalpur. These five districts are the epicentres of exclusion. The sheer scale of potential disenfranchisement – 1 in 7 voters in Gopalganj, 1 in 8 in Purnia – makes these regions extraordinarily volatile.
• Tier 2: High risk (ADR 8-10%): A large and politically diverse group of 13 districts, including Saharsa, Sitamarhi, Samastipur, Saran, Bhojpur, and Siwan. This tier demonstrates that the problem is statewide, extending far beyond a single region.
• Tier 3: Moderate to low risk (ADR < 8%): This group includes 20 districts. While the relative risk is lower, a 6-7% flag rate in a district like Darbhanga or Jamui is more than enough to flip assembly seats decided by narrow margins.

2. The heartland anomaly: Gopalganj, Saran, and Siwan
   The most profound insight comes from the districts where our initial model massively underestimated the risk. Gopalganj ( 20 ranks), Saran ( 20), and Bhojpur ( 21) are the biggest outliers. The common factor here is high out-migration from Bihar's primary labour-exporting belt. It is highly probable that a vast number of registered electors working elsewhere were not physically present to provide documentation. The political implication is a direct threat to the RJD's core 'M-Y' vote bank in its traditional heartland.
3. The urban precarity thesis: Confirmed and expanded
   Our model underestimated the risk in urban centres, and the final data confirms this with startling clarity. Bhagalpur (#5 most at-risk, ADR 10.19%, a 19 rank jump) and Patna (#19 most at-risk, ADR 7.84%, a 17 rank jump) are prime examples. The documentation crisis seems to demonstrably also be an urban phenomenon, disproportionately affecting migrant labourers, renters, and informal workers who lack permanent proof of residence.
4. The Seemanchal-Mithilanchal vulnerability is real
   Our initial thesis, that the intersection of poverty, deprivation, and minority status creates a vulnerability hotspot, has been confirmed. Purnia (#2), Kishanganj (#3), and Madhubani (#4) are all in the top tier of actual risk. This validates the "multiplier effect" theory that the MGB and All India Majlis-e-Ittehadul Muslimeen's political fortunes rest on these exact communities who are now the most susceptible to being struck from voter rolls.
5. The overestimation: Araria, Paschim Champaran, Darbhanga
   Equally insightful is where the risk was lower than predicted. Araria (dropped -21 ranks), Paschim Champaran (-22), and Darbhanga (-19) saw their relative risk fall. This does not mean they are safe – their ADRs of 7-8% are still significant.

Electoral fallout: Connecting disenfranchisement to political power

Raw numbers only tell half the story. The true impact becomes clear when we overlay this risk map onto Bihar's political landscape from the 2020 assembly election.

Unified Master Analysis Table: Disenfranchisement Risk vs. Political Landscape (2020)

This unified table allows for a clear political analysis.

1. The direct assault on MGB strongholds
   Saran (#11 risk), Bhojpur (#12 risk), and Siwan (#14 risk) are MGB bastions now confirmed as high-risk zones. The same pattern holds in the MGB's urban stronghold of Patna (#19 risk, 9 MGB seats) and its bastions in the Magadh region like Aurangabad (#16 risk, 8.30% ADR), which the alliance swept in 2020.
2. Weaponising risk in battleground districts
   The state's key battlegrounds – Samastipur (#10 risk), Vaishali (#15), and Muzaffarpur (#18) – all face ADRs above 8%. In such competitive environments, disenfranchising a small percentage of an opponent's core voters is enough to flip multiple seats. Madhepura (#8 risk, 9.32% ADR), which was split 2-2, is the perfect microcosm.
3. Cementing power in NDA strongholds
   High risk in NDA strongholds like Madhubani (#4 risk) does not harm the ruling alliance. It suppresses the opposition's floor. Widespread disenfranchisement of the MGB's base voters in these districts could crush opposition morale and lead to massive victory margins for the NDA.
4. The Seemanchal equation: Fracturing the anti-NDA vote
   In Kishanganj (#3 risk) and Purnia (#2 risk), the anti-NDA vote was split in 2020 between the MGB and AIMIM. High disenfranchisement risk among the Muslim community, the core base for both, not only weakens the MGB but could completely wipe out AIMIM's presence. The sole beneficiary of this fractured opposition vote is the NDA.

Is this an administrative process or political weapon?

The voter roll revision process has created a potential disenfranchisement crisis for over 65 lakh people, with a profoundly asymmetrical political impact. The crisis has three distinct epicentres:

1. The Migration belt (Gopalganj, Saran, Siwan), threatening the RJD's core voter base.
2. The Urban centres (Bhagalpur, Patna), threatening the urban poor and Dalit vote.
3. The Seemanchal-Mithilanchal arc (Purnia, Kishanganj, Madhubani), threatening the consolidated minority vote crucial for the MGB and AIMIM.

The data tells an unambiguous story: the voter roll revision has created a crisis concentrated in three distinct epicentres, each a bedrock of opposition support, threatening to systematically re-engineer Bihar’s political landscape in the upcoming state elections. The EC’s voter roll revision process, whether by design or by consequence, functions as a highly-effective political weapon. The foreseeable outcome seems to be a fundamental re-engineering of the political landscape in favour of the incumbent alliance.

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