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Democratic Backsliding in the World’s Largest Democracy
Sabyasachi Das*
Ashoka University
July 3, 2023
Abstract
Democratic backsliding is a growing concern globally. This paper contributes to the discussion
by documenting irregular patterns in 2019 general election in India and identifying whether they are
due to electoral manipulation or precise control, i.e., incumbent party’s ability to precisely predict
and affect win margins through campaigning. I compile several new datasets and present evidence
that is consistent with electoral manipulation in closely contested constituencies and is less supportive of the precise control hypothesis. Manipulation appears to take the form of targeted electoral

ygivenx

def bootstrap_ci(data, func, true_col, pred_col, duration_col=None, n_bootstrap=200, alpha=0.05):
    """
    Calculate the confidence interval using bootstrapping.

    Parameters
    ----------
    data: DataFrame
        The data
        
    func: callable

ygivenx

import gzip
import numpy as np
import concurrent.futures

from sklearn.datasets import fetch_20newsgroups

# dataset
newsgroups_train = fetch_20newsgroups(subset='train')
newsgroups_test = fetch_20newsgroups(subset='test')

ygivenx

"""
This script renames the daily files from roam research
to an specified format - 1900-12-25-Sunday.md

Change the default_date_fmt to your required Daily Note Format

Usage:
--------
pip install typer[all]

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"""
Author: Rohan Singh (singhrohan@outlook.com)

Use this code to send yourself a message when a relevant one appears in the `group_name`
Also, get notifications on mac

Usage
===========

Go to: https://my.telegram.org to create an app

ygivenx

a = ['[\\n\\t', 'print(f"a = [{a}]")', 'for i in range(1, len(a)):', "\tprint(f'{a[i]}')\n\t"]
print(f"a = [{a}]")
for i in range(1, len(a)):
	print(f'{a[i]}')

ygivenx

keyword,count
roamresearch,12
notionhq,6
heyhey,5
ouraring,3
readwiseio,3
copilotmoney,3
mmhmmapp,3
chalkapp,3
gmail,3

ygivenx

import logging
import os

LOG_FORMAT = '%(asctime)s %(name)s %(levelname)s %(funcName)s %(lineno)s ClaimID: %(claim_id)s: %(message)s'


class AppLogger(logging.Logger):

    # Override all levels similarly - only info overriden here

ygivenx

{
	"Just Capital": "https://justcapital.com/reports/the-covid-19-corporate-response-tracker-how-americas-largest-employers-are-treating-stakeholders-amid-the-coronavirus-crisis/",
	"The Korean Clusters": "https://graphics.reuters.com/CHINA-HEALTH-SOUTHKOREA-CLUSTERS/0100B5G33SB/index.html",
	"World Central Kitchen": "http://wck.org/",
	"Spillover": "https://wwnorton.com/books/spillover/",
	"Podcast about Spillover": "https://www.scientificamerican.com/podcast/episode/david-quammen-the-spillover-of-anim-12-11-18/",
	"From Bats to Human Lungs, the Evolution of a Coronavirus": "https://www.newyorker.com/science/elements/from-bats-to-human-lungs-the-evolution-of-a-coronavirus",
	"DonorsChoose.org": "http://donorschoose.org/",
	"Li Ziqi": "https://www.sixthtone.com/news/1005007/how-li-ziqi-repackages-rural-china-for-urban-fantasies",
	"Bon Appetit YouTube Channel": "https://www.youtube.com/user/BonAppetitDotCom",

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import re
import pandas as pd
from collections import defaultdict
 
 
def parse_text(data_blocks):
   """
   Generate a dict which could be converted easily to a pandas dataframe
   :param data_blocks: splittable data
   :return: dict with row values for every column