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Election Commission Publishes Second Supplementary Voter List in Bengal
The Election Commission updated West Bengal’s voter rolls without disclosing changes, following a pruning of 58 lakh names in the Special Intensive Revision exercise.
- On Friday night, the Election Commission published the second supplementary voter list under the Special Intensive Revision process for West Bengal, though booth-wise data faced "technical glitches" limiting access to deletion and inclusion details.
- The Supreme Court ordered judicial officers to oversee the revision after a dispute between the Trinamool Congress government and the Election Commission over approximately 60 lakh names flagged as doubtful or pending review.
- Since March 23, officials have resolved an additional 8 lakh cases, bringing the total disposed by 705 judicial officers to over 37 lakh adjudication cases, while more than 23 lakh remain pending.
- Former High Court judge Sahidullah Munshi described his name's deletion as "very humiliating and painful," while West Bengal CEO Manoj Agarwal confirmed individuals may challenge exclusions before appellate tribunals established by the Calcutta High Court.
- With elections scheduled for April 23 and 29, the adjudication process continues under direct supervision of the Chief Justice of the Calcutta High Court to finalize electoral rolls before the state assembly polls.
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13 Articles
13 Articles
No dispute now: Ex-Calcutta HC judge after name appears on SIR list
Justice Sahidullah Munshi, a retired Calcutta High Court judge, clarified on Saturday, March 28, that his name, along with his wife and son, has now appeared in the second supplementary Special Intensive Revision (SIR) list published late Friday, March 27. “In the second supplementary list published, it was shown that our names have been cleared. Now it seems that there is no dispute,” he told Bar and Bench. Munshi, who is also the West Bengal W…
Coverage Details
Total News Sources13
Leaning Left4Leaning Right5Center0Last UpdatedBias Distribution56% Right
Bias Distribution
- 56% of the sources lean Right
56% Right
L 44%
R 56%
Factuality
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