According to India's last census in 2011, about 14.2 percent of the total population identified as Muslims. This was an increase from about ten percent in 1951. Overall, India has been a religiously pluralistic and multiethnic democracy with people of several faiths.

According to India's last census in 2011, the Muslim population had about 24.6 percent of decadal growth rate, while Hindus had a decadal growth rate of 16.8 percent. India, a secular nation provides religious freedom as a fundamental right under the constitution to its citizens.

According to a survey conducted between 2013 and 2014 across India, **** percent of the heads of households in the country identified as Hindu, followed by **** percent of Muslim heads of households. This is a direct indicator that although religiously pluralistic, India is a largely Hindu nation.

It was estimated that by 2050, India's Muslim population would grow by ** percent compared to 2010. For followers of the Hindu faith, this change stood at ** percent. According to this projection, the south Asian country would be home not just to the world's majority of Hindus, but also Muslims by this time period. Regardless, the latter would continue to remain a minority within the country at ** percent, with ** percent or *** billion Hindus at the forefront by 2050.

India General Election: State Parties: Kerala: Muslim League Kerala State Committee: Number of Candidates: Seats Won data was reported at 2.000 Person in 2014. This stayed constant from the previous number of 2.000 Person for 2009. India General Election: State Parties: Kerala: Muslim League Kerala State Committee: Number of Candidates: Seats Won data is updated yearly, averaging 2.000 Person from Mar 1962 (Median) to 2014, with 14 observations. The data reached an all-time high of 2.000 Person in 2014 and a record low of 1.000 Person in 2004. India General Election: State Parties: Kerala: Muslim League Kerala State Committee: Number of Candidates: Seats Won data remains active status in CEIC and is reported by Election Commission of India. The data is categorized under India Premium Database’s General Election – Table IN.GEC019: General Election: Loksabha: Performance of State Parties: Kerala.

The share of the Muslim Members of Parliament (MPs) in 2024 Lok Sabha shrunk to 4.42 percent, a decrease from the previous year. This was the second-lowest share since 1952. Muslim representation was the weakest in the election year 2014 and the highest in 1980.

Kerala: Malappuram: Total Votes Polled: Indian Union Muslim League data was reported at 589,873.000 Unit in 03-01-2019. This records an increase from the previous number of 437,723.000 Unit for 03-01-2014. Kerala: Malappuram: Total Votes Polled: Indian Union Muslim League data is updated quinquennially, averaging 513,798.000 Unit from Mar 2014 (Median) to 03-01-2019, with 2 observations. The data reached an all-time high of 589,873.000 Unit in 03-01-2019 and a record low of 437,723.000 Unit in 03-01-2014. Kerala: Malappuram: Total Votes Polled: Indian Union Muslim League data remains active status in CEIC and is reported by Election Commission of India. The data is categorized under India Premium Database’s General Election – Table IN.GEA017: General Election: Loksabha: Election Outcome of Parliamentary Constituencies: Kerala.

West Bengal: Tamluk: Total Votes Polled: Indian Union Muslim League data was reported at 1,500.000 Unit in 2014. West Bengal: Tamluk: Total Votes Polled: Indian Union Muslim League data is updated yearly, averaging 1,500.000 Unit from Mar 2014 (Median) to 2014, with 1 observations. West Bengal: Tamluk: Total Votes Polled: Indian Union Muslim League data remains active status in CEIC and is reported by Election Commission of India. The data is categorized under India Premium Database’s General Election – Table IN.GEA035: General Election: Loksabha: Election Outcome of Parliamentary Constituencies: West Bengal.

Poverty and empowerment impacts of the Bihar Rural Livelihoods Project: Evidence from a Mixed-Methods Cluster-Randomized Trial Jeevika is a World Bank assisted project focussed (now under the umbrella of the NRLM) on building networks of women's self-help credit and savings groups,and then using them as a base of other "vertical" interventions. This houshold and village survey data was collected over two rounds to conduct an impact evaluation of Phase 2 of the project with random assignment of the project over a two year period. Collaboration: World Bank Social Observatory team with Government of Bihar. Evaluation design, methods and implementation In order to evaluate the impacts of Jeevika, 180 panchayats were randomly selected from within 16 blocks in seven districts where scale-up of the project was planned but had not yet occurred. Some of these blocks were in districts relatively far from Patna, which had not yet been entered by the project (Madhepura, Saharsa, Supaul), while others were within the larger districts within which Jeevika was already operating (Gaya, Nalanda, Madhubani, Muzaffarpur). The project had already entered these districts in Phase 1, but had not yet expanded to all blocks due to (project) capacity constraints. Within each of the study villages, hamlets (tolas) in which the majority of the population belonged to a scheduled caste or scheduled tribe were identified. This was the same procedure as used by Jeevika to identify the target population (of poor women) for mobilization into the project. Tolas were identified through a focus group discussion held in each village, along with the population of target castes (SC/STs) within each. In Bihar, tola boundaries are easily distinguishable. Field teams would enter the tola at a random point, determine the skip pattern based on the population size and target sample size, and select households through a random walk. Survey staff aimed to include 70% SC/ST households, and 30% households from other castes in each village, in order to ensure variation in socio-economic status within the sample. If the households in selected tolas included fewer SC/ST households than this, households from nearby non-SC/ST majority tolas were also included in the sample. Interviews for the quantitative study were conducted using a structured paper survey form. Baseline and follow up surveys included detailed questions on debt, asset holdings, consumption expenditures, livelihood activities, and women’s mobility, role in household decisions, and aspirations. In addition, in each village, a focus group discussion was conducted, through which data were collected on village level attributes such as local sources of credit, interest rates from each source, local wage rates, and the presence of or distance to markets and other institutions and amenities. Respondents were not compensated for their time. If a respondent was unavailable during initial field visit, the supervisor recorded contact details and returned with interviewers at a later date. As long as the survey team was in that district, repeat visits were undertaken, keeping attrition to a minimum. If a household could not be re-surveyed at endline, it was replaced with another household in the same village. Short re-surveys containing a subset of questions from the main survey were conducted by supervisors for 10% of the sample. Staff from the project also conducted occasional visits after the survey was completed in a village to confirm that all modules had been covered by survey staff. Data was entered in duplicate using CSPro and any discrepancies were corrected based on the paper form. Following the baseline survey, panchayats were stratified on the 16 administrative blocks in the sample and the panchayat-level mean of outstanding high cost (monthly interest rate of 4% or higher) debt held by households at baseline. They were then randomly assigned to an early rollout group or a late rollout group using the random number generator within the Stata statistical analysis software package. The baseline survey was administered to 8988 households across 333 villages in 179 panchayats. The target number of households per panchayat was 50, but there was some variation around this in reality. The lowest number of households in a given panchayat was 49 (9 panchayats), and the largest number was 53 households (3 panchayats). To ensure that control panchayats were not entered by the project, Jeevika held a quarterly ""evaluation panchayat"" meeting, which block project managers of the 16 blocks were required to attend. At these meetings the project M&E team checked whether any village in a control panchayat had been entered, and received an update on progress in treatment panchayats. This procedure was successful in maintaining adherence to randomized treatment assignment throughout the evaluation period. Of the 4,472 households in the sample across 89 panchayats allocated to receive the SHG intervention, 2,722 reported that one of their members belonged to an SHG by endline, constituting 61% of the sample. Since SHG membership was optional, approximately 38% of households in treatment group panchayats had no member in an SHG by endline. The remaining 56 households (across 39 panchayats) did not answer this question or were lost to follow-up (only one such household was not replaced). Although it was possible for those residing in control areas to join (non-Jeevika) SHGs, the proportion of households group in this area containing SHG members remained minimal at endline, with only 460 households (just over 10% of the total sample) reporting SHG membership. Attrition (and replacement) were similar in control and treatment arms, with 132 treatment group baseline households not reached for a follow-up interview and all but one of these replaced, and 128 not reached and thus replaced in the control group. The qualitative evaluation draws on data collected from 2011 to early 2015 in six villages, two where Jeevika had been operating since 2006, two it entered during Phase II, and two where it had not yet intervened by the end of data collection. The Phase I treatment villages were selected at random from the set of previously entered villages in two different districts – Muzaffarpur and Madhubani. Each treatment village was then matched with a set of control villages using propensity score matching methods (Imbens and Rubin 2015) on the basis of village level data from the 2001 government census on literacy, caste composition, landlessness, levels of outmigration, and the availability of infrastructure. In order to find the closest treatment-control match, field investigators then visited the set of possible controls for two days for visual inspection and qualitative assessment. This combined quantitative and qualitative matching method yielded three matched pairs of phase I treatment, phase II treatment, and control villages, with each pair located within the same district. This method of sample selection allows comparison of villages receiving the intervention at each stage with their statistical clones that received it at a different stage or had not received it at all, allowing us to draw causal inferences about the effects induced by Jeevika during the different phases of its expansion. For the purpose of keeping their identity anonymous, we refer to the villages in Madhubani district as Ramganj (Phase I treatment), Nauganj (Phase II treatment) and Virganj (control) and the villages in Muzaffarpur district Saifpur (Phase I treatment), Raipur (Phase II treatment) and Bhimpur (Control). Villages in Madhubani are divided into segregated and caste-homogenous tolas. Brahmins are a majority in these villages, and their tolas are located close to the main resources of the village: the temple, pond and school. All other tolas extend southwards in decreasing order of status in the caste hierarchy, with the Schedule Caste (SC) communities being located farthest south. Each of these communities is also spatially segregated. The SC communities of these villages are mainly comprised of Musahar, Pasi, Ram, and Dhobi subcastes, and the other backward caste communities are comprised of Yadav, Mandal, Badhai, Hajaam, and Teli subcastes. The only big difference between Ramganj and Virganj is that the former has a sizeable Muslim population, comprising Sheikhs, Ansaris, Nutts and Pamariyas, while in the latter, there is only one Muslim (Sheikh) family in the entire village. Inhabitants of these villages primarily depend on agriculture and related activities for their livelihood. The villages in Muzaffarpur district are largely similar to the ones in Madhubani with the important differences being that they are primarily bazaar (market)-centric and the dominant caste is the Chaudhury, who belong to the business community. In each of these villages, first, preliminary studies were conducted using several participatory rural appraisal methods to gain an understanding of the layout of the village. Following this, a team of four field investigators (recruited from a local research-based NGO) accompanied by one of the three principal researchers would visit the villages every three to four months for a cycle of data collection (11 in total over the study period). During every cycle, the ethnographers would enter a different tola in the village for a week (there are roughly 10 tolas in each village). The ethnographers spoke to as many respondents as possible across the village and also returned to the first few respondents in the concluding cycles of data collection. These repeat interviews allowed us to see how respondents reflected on changes experienced as a result of the project [or otherwise] over the four-year period. The first set of participants was selected to be representative of different socioeconomic strata in the village, and subsequent participants were selected via a mixture of purposive and snowball sampling. We

General Election: State Parties: Kerala: Muslim League Kerala State Committee: Number of Candidates: Seats Won在2014达2.000 人口，相较于2009的2.000 人口保持不变。General Election: State Parties: Kerala: Muslim League Kerala State Committee: Number of Candidates: Seats Won数据按每年更新，1962至2014期间平均值为2.000 人口，共14份观测结果。该数据的历史最高值出现于2014，达2.000 人口，而历史最低值则出现于2004，为1.000 人口。CEIC提供的General Election: State Parties: Kerala: Muslim League Kerala State Committee: Number of Candidates: Seats Won数据处于定期更新的状态，数据来源于Election Commission of India，数据归类于India Premium Database的General Election – Table IN.GEC019: General Election: Loksabha: Performance of State Parties: Kerala。