Appeals 1930, part 7, state IB: Distinction of persons in position D and of persons for whom no distinction according to position has been made (persons in classes XXIV et seq.) according to profession and according to age, sex and marital status, for the total of the Empire. Among the "Unemployed" and "The entire population" 37 men and 9 women, whose marital status is not known, are not included in the figures. Data available for: 1930 Status of the figures: The data in this table are final. Changes as of June 8, 2018: None, this table has been discontinued. When will new numbers come out? Not applicable anymore.

This data collection contains information about total population and total number of professionally employed within the principal occupational groups agriculture and subsidiary industry, industry and craft, commerce and shipping, public service and independent professions, domestic work, and former professionally employed, and also within subgroups of these principal groups.

PERIOD: 1930. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

Occupational Census 1930, part 7, state IA: Distinction of persons in position A, B and C according to occupational classes and occupational groups and according to age, sex and marital status, for the whole of the Reich. Data available for: 1930 Status of the figures: The data in this table are final. Changes as of June 8, 2018: None, this table has been discontinued. When will new numbers come out? Not applicable anymore.

PERIOD: 1930. NOTE: (In thousands.) The sequel is a percentage of the total population. SOURCE: [Statistics and reports of major countries].

This dataset comprises data on occupations of the Dutch censuses of 1909, 1920 and 1930, and includes information on sex, occupational class and number of occurrences.

PERIOD: 1930. NOTE: (In thousands). SOURCE: [Statistics and reports of major countries].

Appeal 1930, Part 7, state I: distinction of persons practising a profession, by business classes, business groups and professions, in the economic-geographical parts of the Empire, indicating the position in the profession and of the sex.

Data available for: 1930

Status of the figures: The data in this table are final.

Changes as of 4 June 2018: None, this table has been discontinued.

When are new figures coming? No longer applicable.

This database, including both datasets and spatial shape files, contains information on occupation, school attendance, nativity, and race of the Boston population, by ward, for the years 1880, 1900, and 1930. This database can be used to visualize the profound changes in the economic, educational, and ethnic composition of Boston between 1880 and 1930. It illustrates, among other changes, the great expansion of secondary school enrollment, the decline of youth participation in the work force, the growth of white-collar jobs, the decline of unskilled labor, and the geographical distribution of the Boston Irish, Italian, Jewish, and African-American populations over time. This contextual knowledge is useful for historians researching this time period, and useful to non-historians by depicting the origins of fundamental changes whose legacy is still present in Boston today. The underlying data are drawn from the Integrated Public Use Microdata Series maintained by the University of Minnesota (see documentation for full citation). The data contained here can also be viewed through an interactive map hosted by BostonMap (http://worldmap.harvard.edu/maps/historical_boston).

PERIOD: 1930. NOTE: (In thousands). SOURCE: [Statistics and reports of major countries].

Abstract copyright UK Data Service and data collection copyright owner.

This study aimed to explore the ways in which male students calculated the costs and benefits of higher education in England in the 1930s, before the establishment of mandatory grants and awards; together with an analysis of the strategies used for meeting the costs of this investment. It was designed to complement the researcher's earlier study of women graduates of the same period, which was carried out in 1995 with support from the Spencer Foundation in Chicago.
Main Topics:

A total of 1085 four page questionnaires were distributed to men who had graduated from eight English universities and university colleges before 1939. Respondents were asked to give information about their social background and the ways in which they had met the expense of their years at college. They were also asked about their subsequent careers. A total of 577 completed questionnaires were obtained.

This database contains only that material, extracted from the completed questionnaires, which could be effectively anonymised. Entries give information about family of origin and family of destination. They give some indication of reasons for going to university. The bulk of the information relates to family support and type of funding.

Main variables: institution, father's occupation, mother's occupation, family of origin size, reasons for going to university, arts or sciences, subject, degree result, extent of family funding, state scholarship, local authority scholarship, board of education grant, school scholarship, university/college scholarship, loans taken out, other sources of support, teaching qualification, place of residence, vacation work, first occupation, other occupations, marital status, number of children, wife's occupation before marriage, wife's employment status after marriage, notes.

The original questionnaires remain in the possession of the depositor and access is embargoed.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

One aim of the Soviet Union, and communist countries in general, was to achieve full employment. Official policy was designed to prevent unemployment, and the state stopped paying most unemployment benefits in the 1930s. Every citizen had the right (or requirement) to work, and jobs were allocated by the state, not competed for as they were in the west. People could apply for certain positions, based on their education, experience, or interests, but roles could often be distributed to meet employment demands, or preferential roles were distributed via nepotism. The socialist economic system removed job market competition, which provided increased job security but removed many of the incentives that boosted productivity (especially in later decades). In the 1970s and 1980s, average work weeks were under 35 hours long and people retired in their mid to late fifties. Compared to the U.S. in 1985, on average, work weeks were around four hours shorter in the USSR, and Soviet men retired five years earlier, while women retired nine years earlier than their American counterparts.

Wages In earlier years, wages had been tied to individual performance or output, however the de-Stalinization process of the 1960s introduced a more standardized system of payment; from this point onwards, base wages were more fixed, and bonuses had a larger impact on disposable income. Personal finances in the Soviet Union were very different from those in the west; wages were split into base salaries and bonuses, along with a social wage that was "paid" in the form of investments in housing, healthcare, education, and infrastructure, as well as subsidized vouchers for holidays and food. Many of these amenities were also provided by the state, which removed the individual costs that were required across the west and in post-Soviet states today. Overall, income and money in general had a much lower influence on daily life in the USSR than it did in the west, lessening factors such as financial stress and indebtedness, but restricting consumeristic freedom.

Gender differences A major difference between the East and West Blocs was the participation rate of women in the workforce. Throughout most of the USSR's history, women made up the majority of the workforce, with a 51.4 percent share in 1970, and 50.4 percent in 1989; in the U.S. figures for these years were 38 and 45 percent respectively. Although this was due to the fact that women also made up a larger share of the total population (around 53 percent in this period), Soviet women were possibly the most economically active in the world in these decades. When comparing activity rates of women aged between 40 and 44 across Europe in 1985, the USSR had a participation rate of 97 percent; this was the highest in the East Bloc (where rates ranged from 85 to 93 percent in other countries), and is much higher than rates in Northern Europe (71 percent), Western Europe (56 percent) and Southern Europe (37 percent).

Abstract

China Living Standards Survey (CLSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.

Geographic coverage

The China Living Standards Survey (CLSS) was conducted only in Hebei and Liaoning Provinces (northern and northeast China).

Kind of data

Sample survey data [ssd]

Sampling procedure

The CLSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in Northeastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930’s. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930’s. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus the intended sample size was 780 households, 130 from each county.

Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list.

In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire

The household questionnaire contains sections that collect data on household demographic structure, education, housing conditions, land, agricultural management, household non-agricultural business, household expenditures, gifts, remittances and other income sources, and saving and loans. For some sections (general household information, schooling, housing, gift-exchange, remittance, other income, and credit and savings) the individual designated by the household members as the household head provided responses. For some other sections (farm land, agricultural management, family-run non-farm business, and household consumption expenditure) a member identified as the most knowledgeable provided responses. Identification codes for respondents of different sections indicate who provided the information. In sections where the information collected pertains to individuals (employment), whenever possible, each member of the household was asked to respond for himself or herself, except that parents were allowed to respond for younger children. Therefore, in the case of the employment section it is possible that the information was not provided by the relevant person; variables in this section indicate when this is true.

The household questionnaire was completed in a one-time interview in the summer of 1995. The survey was designed so that more sensitive issues such as credit and savings were discussed near the end. The content of each section is briefly described below.

Section 0 SURVEY INFORMATION

This section mainly summarizes the results of the survey visits. The following information was entered into the computer: whether the survey and the data entry were completed, codes of supervisor’s brief comments on interviewer, data entry operator, and related revising suggestion (e.g., 1. good, 2. revise at office, and 3. re-interview needed). Information about the date of interview, the names of interviewer, supervisor, data enterer, and detail notes of interviewer and supervisor were not entered into the computer.

Section 1 GENERAL HOUSEHOLD INFORMATION

1A HOUSEHOLD STRUCTURE 1B INFORMATION ABOUT THE HOUSEHOLD MEMBERS’ PARENTS 1C INFORMATION ABOUT THE CHILDREN WHO ARE NOT LIVING IN HOME

Section 1A lists the personal id code, sex, relationship to the household head, ethnic group, type of resident permit (agricultural [nongye], non-agricultural [fei nongye], or no resident permit), date of birth, marital status of all people who spent the previous night in that household and for household members who are temporarily away from home. The household head is listed first and receives the personal id code 1. Household members were defined to include “all the people who normally live and eat their meals together in this dwelling.” Those who were absent more than nine of the last twelve months were excluded, except for the head of household. For individuals who are married and whose spouse resides in the household, the personal id number of the spouse is noted. By doing so, information on the spouse can be collected by appropriately merging information from the section 1A and other parts of the survey.

Section 1B collects information on the parents of all household members. For individuals whose parents reside in the household, parents’ personal id numbers are noted, and information can be obtained by appropriately merging information from other parts of the survey. For individuals whose parents do not reside in the household, information is recorded on whether each parent is alive, as well as their schooling and occupation.

Section 1C collects information for children of household members who are not living in home. Children who have died are not included. The information on the name, sex, types of resident permit, age, education level, education cost, reasons not living in home, current living place, and type of job of each such child is recorded.

Section 2 SCHOOLING

In Section 2, information about literacy and numeracy, school attendance, completion, and current enrollment for all household members of preschool age and older. The interpretation of pre-school age appears to have varied, with the result that while education information is available for some children of pre-school age, not all pre-school children were included in this section. But for ages 6 and above information is available for nearly all individuals, so in essence the data on schooling can be said to apply all persons 6 age and above. For those who were enrolled in school at the time of the survey, information was also collected on school attendance, expenses, and scholarships. If applicable, information on serving as an apprentice, technical or professional training was also collected.

Section 3 EMPLOYMENT

3A GENERAL INFORMATION 3B MAJOR NON-FARM JOB IN 1994 3C THE SECOND NON-FARM JOB IN 1994 3D OTHER EMPLOYMENT ACTIVITIES IN 1994 3E SEARCHING FOR NON-FARM JOB 3F PROCESS FOR GETTING MAJOR NON-FARM JOB 3G CORVEE LABOR

All individuals age thirteen and above were asked to respond to the employment activity questions in Section 3. Section 3A collects general information on farm and non-farm employment, such as whether or not the household member worked on household own farm in 1994, when was the last year the member worked on own farm if he/she did not work in 1994, work days and hours during busy season, occupation and sector codes of the major, second, and third non-farm jobs, work days and total income of these non-farm jobs. There is a variable which indicates whether or not the individual responded for himself or herself.

Sections 3B and 3C collect detailed information on the major and the second non-farm job. Information includes number of months worked and which month in 1994 the member worked on these jobs, average works days (or hours) per month (per day), total number of years worked for these jobs by the end of 1994, different components of income, type of employment contracts. Information on employer’s ownership type and location was also collected.

Section 3D collects information on average hours spent doing chores and housework at home every day during non-busy and busy season. The chores refer to cooking, laundry, cleaning, shopping, cutting woods, as well as small-scale farm yard animals raising, for example, pigs or chickens. Large-scale animal

PERIOD: Population census on Oct. 1, 1930. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

Once a major powerhouse of the British economy, the coal mining industry was the lifeblood of several regions, providing employment to more than *********** workers before the 1930s. Since that time, shifting attitudes towards coal and the emergence of alternative energy sources such as wind and solar have seen coal's role in the UK's energy mix diminish. By 1990, the coal industry was still an employer to some ****** people, however from 2016 onwards, this figure had fallen to less than ************. Coal mines in the UK As of 2023, there were ***** UK coal mines left in operation. Of these, *** was an opencast site and *** were deep mines. The British government has made it clear that phasing out coal is necessary for the country to reach its goal of carbon neutrality by 2050. The industry is thus set to further contract in the future. Coal job cuts globally The shrinking number of jobs has not been isolated to the UK, with similar coal mining employment reductions in the United States. In some U.S. states, such as Kentucky, coal mining jobs had fallen by more than ************** in the past *** years. In Australia, where coal mining has traditionally been as strong contributor to the economy, this decreasing trend is also visible.

Samples from various features at the late nineteenth/early twentieth century Lambert farmstead site in Mountainburg, Crawford County, Arkansas, were examined for macrofloral remains. This site was occupied by the Lambert family from roughly the 1930s to the 1940s. Features at the site include a three-room main house, a smaller "guest house", a possible smoker/evaporator, a shed/kitchen annex, a root cellar/barn, an animal pen, a stone table/well, a privy, a trash pit, a sheet midden, and various other stone features. It is believed that the Lambert family's experience is typical of many Americans in the midwestern United States during the Depression. The Ozarks became a refuge from the "big city" where several families lost their jobs in the early 1930s. Macrofloral analysis is used to provide information concerning diet, including use of indigenous and possibly introduced species of plant resources as food. Macrofloral analysis may also provide insight into historic plants found in garden areas, and possibly resources associated with occupations of the site prior to that by the Lambert family.

PERIOD: Population census on Oct. 1, 1930. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

PERIOD: Oct. 1, 1930. NOTE: The unemployed are classified based on their last occupation before becoming unemployed. SOURCE: Population Census of Japan; [Survey by the Statistics Bureau, Imperial Cabinet].

PERIOD: As of Oct. 10, 1930. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

PERIOD: Population census on Oct. 1, 1930. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].