The population of India is divided into several groups based on social, educational, and financial statuses. The formation of these groups is a result of the historical social structure of the country. Between 2019 and 2021, Other Backward Class (OBC) constituted the largest part of Indian households accounting for about ** percent. On the other hand, Schedule Tribes formed about *** percent of households. How prosperous is India’s caste-based society? India suffers from extreme social and economic inequality. The combined share of Schedule Tribe and Schedule Caste in the affluent population of India was less than ** percent. Contrary to this, economically and socially stronger groups constituted the major part of the affluent population. Hence, indicating a strong relationship between caste and prosperity. India’s thoughts on caste-based reservation The constitution of India provides reservations to the weaker sections of the society for their upliftment and growth. However, the need for reservation has increased with time, making the whole situation even more complicated. People are divided over the existence of a system that provides preference to certain castes or sects. In a survey conducted in 2016 about providing employment reservation to young adults of Schedule Caste and Schedule Tribe, many people expressed opposition. More than ** percent of opposition came from upper Hindu caste. Minimum opposition was observed from the people belonging to Schedule Tribe and Schedule Caste.

This statistic displays the results of a survey about the share of affluent population across India in fiscal year 2016, based on caste. During the measured time period, approximately ** percent of the Muslim population across the country were considered affluent.

India Census: Population: by Religion: Hindu: Male data was reported at 498,306,968.000 Person in 2011. This records an increase from the previous number of 428,678,554.000 Person for 2001. India Census: Population: by Religion: Hindu: Male data is updated yearly, averaging 463,492,761.000 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 498,306,968.000 Person in 2011 and a record low of 428,678,554.000 Person in 2001. India Census: Population: by Religion: Hindu: Male data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

The literacy rate of the total population in the country was about 73 percent in 2011, in comparison to about 66 percent among the scheduled caste population. In India, scheduled caste and scheduled tribe and other backward class are officially recognized by the constitution as groups of disadvantaged indigenous people. They are the primary beneficiaries of reservation policies under the constitution.

The dataset contains Year- and region-wise All India compiled data on distribution (per thousand) of Scheduled Caste (SC), Scheduled Tribe (ST), Other Backward Classes (OBC) and Others caste households by agricultural activity undertaken different sizes of agricultural land, during the period of 2005 to 2012. The dataset has been compiled from Statement Nos. 3.8 of 61st, 66th and 68th round reports of NSS.

India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

This dataset contains the State, Year, Caste, Level and Gender-wise Gross Enrolment Ratio (GER) in India. The Gross Enrolment Ratio (GER) compares the enrolment in a specific level of education to the population of the age-group which is most age-appropriate for that level of educationThe data is given for all caste categories, Scheduled Castes and Scheduled Tribes.

In modern times, the whole world is divided into different subjects. In this, Indian economic inequality is divided into different sections of tradition. They are poor-rich, unequal distribution of income, caste, religion, gender, etc. Is divided on the basis of. In this, caste-based inequality is detrimental to Indian economic development. Caste was created in Indian society as a system of income and distribution in the society. Caste is omnipresently governed by different and peculiar traditional rules and norms. Therefore, it can be said that in a caste-based economy, business and property rights are inherited as well as hereditary, and each caste is forced to keep them the same. All the castes in India are based on this socialization. Although conversion is possible in India, caste cannot be changed under any circumstances. A person who is born in the same caste dies in the same caste. In India, it is called caste discrimination that creates castes at this social level. In the literature of modern economics, the concept of exclusion and economic discrimination is considered to be related to race, caste, or gender.

The dataset contains year-, region-, social-group- and gender-wise All India compiled data on per thousand distribution of scheduled caste, tribe, other backwards classes and other people by their different levels of education such as literate, non-literate, literate upto primary, primary, secondary, middle, higher secondary, graduate and above, post graduate and above levels of education. The dataset has been compiled from table nos. 8, s3.13 and statement nos. 3.13.1 and 3.12.1 of NSS 55th, 61st, 66th and 68th rounds published from the year 2000 to 2012.

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 tr... Visit https://dataone.org/datasets/sha256%3A33337f03a8c2dabc0a718655e958c47678381b39ee277e0c820aeca2b66a6db8 for complete metadata about this dataset.

The dataset contains Year-, region- and gender-wise All India compiled data on caste-wise (scheduled caste (SC), scheduled tribe (ST), other backwards classes (OBC) and others) distribution (per thousand) of rural and urban households by different types of employment such self-employment, salaried, regular wage, casual labour, etc., during the period of 2000 to 2012. The dataset has been compiled from Table Nos. Table 3, Statement Nos. 3.5 and 3.6 of 55th, 61st, 66th and 68th report of NSS.

This household questionnaire collects comprehensive socioeconomic and demographic data from families in the Ahmednagar district. It includes details about family structure, such as the head of the family, religion, caste, and relationship of each family member to the head. Information about education, occupation, income, and marital status is recorded, alongside data on living conditions like monthly expenditures, number of rooms, and household amenities (e.g., electricity, mobile phones, vehicles). The survey also assesses assets like livestock ownership and income from animals, building materials used in the home, and the type of cooking fuel. Additionally, it gathers information on the legal ownership of the house and the type of ration card held, reflecting the household's financial status.

The dataset contains Year-, region- and gender-wise All India compiled data on distribution (per thousand) of persons of age group 15 years and above belonging to scheduled caste (SC), scheduled tribe (ST), other backwards classes (OBC) and other castes by Level of Education such as primary, secondary, higher secondary, middle, diploma/certificate, graduate, post graduate, etc., during the period of 2000 to 2012. The dataset has been compiled from Table Nos. 8, 3.13, Statement Nos. 3.12 and 3.13 of 55th, 61st, 66th and 68th reports of NSS.

Prison Inmates in India

Demographics, Age, Education, Caste, Wages, Rehabilitation, Technical Info

By Rajanand Ilangovan [source]

About this dataset

This dataset provides a detailed view of prison inmates in India, including their age, caste, and educational background. It includes information on inmates from all states/union territories for the year 2019 such as the number of male and female inmates aged 16-18 years, 18-30 year old inmates and those above 50 years old. The data also covers total number of penalized prisoners sentenced to death sentence, life imprisonment or executed by the state authorities. Additionally, it provides information regarding the crimehead (type) committed by an inmate along with its grand total across different age groups. This dataset not only sheds light on India’s criminal justice system but also highlights prevelance of crimes in different states and union territories as well as providing insight into crime trends across Indian states over time

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides a comprehensive look at the demographics, crimes and sentences of Indian prison inmates in 2019. The data is broken down by state/union territory, year, crime head, age groups and gender.

This dataset can be used to understand the demographic composition of the prison population in India as well as the types of crimes committed. It can also be used to gain insight into any changes or trends related to sentencing patterns in India over time. Furthermore, this data can provide valuable insight into potential correlations between different demographic factors (such as gender and caste) and specific types of crimes or length of sentences handed out.

To use this dataset effectively there are a few important things to keep in mind: •State/UT - This column refers to individual states or union territories in India where prisons are located •Year – This column indicates which year(s) the data relates to •Both genders - Female columns refer only to female prisoners while male columns refers only to male prisoners •Age Groups – 16-18 years old = 21-30 years old = 31-50 years old = 50+ years old •Crime Head – A broad definition for each type of crime that inmates have been convicted for •No Capital Punishment – The total number sentenced with capital punishment No Life Imprisonment – The total number sentenced with life imprisonment No Executed– The total number executed from death sentence Grand Total–The overall totals for each category

By using this information it is possible to answer questions regarding topics such as sentencing trends, types of crimes committed by different age groups or genders and state-by-state variation amongst other potential queries

Research Ideas

• Using the age and gender information to develop targeted outreach strategies for prisons in order to reduce recidivism rates.
• Creating an AI-based predictive model to predict crime trends by analyzing crime head data from a particular region/state and correlating it with population demographics, economic activity, etc.
• Analyzing the caste of inmates across different states in India in order to understand patterns of discrimination within the criminal justice system

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original.

Columns

File: SLL_Crime_headwise_distribution_of_inmates_who_convicted.csv | Column name | Description | |:--------------------------|:---------------------------------------------------------------------------------------------------| | STATE/UT | Name of the state or union territory where the jail is located. (String) | | YEAR | Year when the inmate population data was collected. (Integer) ...

The catalog contains data related to final population totals, census 2001 - India and States. It includes data on Population, Scheduled Caste Population, Scheduled Tribe Population, SC Population, ST Population, Male Population, Female Population.

The data refers to State/UT-wise and caste-wise details of prison inmates at the end of the reference year. The prison inmates are categorised into male and female population. The age of inmates are grouped into 16-18 yrs, 18-30 yrs, 30-50 yrs and 50 & above yrs. Castes of jail inmates are further categorized as OBCs, SCs, STs & Others.

Abstract

The gigantic task of census taking was completed in two phases. In the first phase, known as House-listing Operations, all building and structures, residential, partly residential or non- residential were identified and listed and the uses to which they were put recorded. Information on houses, household amenities and assets were also collected. In the second phase, known as Population Enumeration, more detailed information on each individual residing in the country, Indian national or otherwise, during the enumeration period was collected. At the Census 2001, more than 2 million (or 20 lakh) enumerators were deployed to collect the information by visiting every household. The Indian Census is one of the largest administrative exercises undertaken in the world.

Geographic coverage

National

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The Household Schedule and the Houselist Schedule are available in English and provided as external resources.

The Household Schedule covers topics including the following: - General and Socio-Cultural characteristics (religion, caste, language, education, disability); Characteristics of workers and non-workers; Migration characteristics; Fertility particulars The Houselist Schedule covers topics including the following: - Floor, wall and roofing material; Use of census house; Drinking water source; Source of lighting; Fuel used for cooking

A study conducted by Oxfam in India revealed that the majority of leadership roles within news organizations across media types were dominated by editors and proprietors belonging to the general category, grossing over ** percent in 2022. Digital media outlets were the only type of news media to have some representation of the SC, ST, and OBC categories at over ** percent, two percent, and five percent respectively.

The literacy rate of the female population in the country was about 65 percent in 2011, in comparison to about 57 percent among the females in the scheduled caste population.

The catalog contains data related to Population Age 5-19 Attending School/ College by Economic Activity Status and Sex (For Each Caste/Tribe Separately), Census 2001 - India and States. It includes data on Scheduled Caste and Scheduled Tribe Population Age 5-19 attending School or College by Economic Activity Status like Main Worker, Marginal Worker, Non-worker.