United States Immigrants Admitted: All Countries data was reported at 1,127,167.000 Person in 2017. This records a decrease from the previous number of 1,183,505.000 Person for 2016. United States Immigrants Admitted: All Countries data is updated yearly, averaging 451,510.000 Person from Sep 1900 (Median) to 2017, with 118 observations. The data reached an all-time high of 1,827,167.000 Person in 1991 and a record low of 23,068.000 Person in 1933. United States Immigrants Admitted: All Countries data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s United States – Table US.G087: Immigration.

Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

This table contains 25 series, with data for years 1955 - 2013 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Last permanent residence (25 items: Total immigrants; France; Great Britain; Total Europe ...).

Estimates for UK immigration, emigration and net migration, year ending June 2012 to year ending June 2024. These are official statistics in development. To access the most up to date data for each time period, please use the most recently published dataset.

The data presented in this data project were collected in the context of two H2020 research projects: ‘Enhanced migration measures from a multidimensional perspective’(HumMingBird) and ‘Crises as opportunities: Towards a level telling field on migration and a new narrative of successful integration’(OPPORTUNITIES). The current survey was fielded to investigate the dynamic interplay between media representations of different migrant groups and the governmental and societal (re)actions to immigration. With these data, we provide more insight into these societal reactions by investigating attitudes rooted in values and worldviews. Through an online survey, we collected quantitative data on attitudes towards:

1. Immigrants, Refugees, Muslims, Hispanics, Venezuelans
2. News Media Consumption
3. Trust in News Media and Societal Institutions
4. Frequency and Valence of Intergroup Contact
5. Realistic and Symbolic Intergroup Threat
6. Right-wing Authoritarianism
7. Social Dominance Orientation
8. Political Efficacy
9. Personality Characteristics
10. Perceived COVID-threat, and
11. Socio-demographic Characteristics

1. Austria
2. Belgium
3. Germany
4. Hungary
5. Italy
6. Spain
7. Sweden

1. United States of America
2. Colombia

The survey in the United States and Colombia was identical to the one in the European countries, although a few extra questions regarding COVID-19 and some region-specific migrant groups (e.g. Venezuelans) were added. We collected the data in cooperation with Bilendi, a Belgian polling agency, and selected the methodology for its cost-effectiveness in cross-country research. Respondents received an e-mail asking them to participate in a survey without specifying the subject matter, which was essential to avoid priming. Three weeks of fieldwork in May and June of 2021 resulted in a dataset of 13,645 respondents (a little over 1500 per country). Sample weights are included in the dataset and can be applied to ensure that the sample is representative for gender and age in each country. The cooperation rate ranged between 12% and 31%, in line with similar online data collections.

This table contains 32 series, with data for years 1956 - 1976 (not all combinations necessarily have data for all years), and was last released on 2012-02-16. This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (32 items: Outside Canada; Great Britain; France; Europe ...).

This database automatically includes metadata, the source of which is the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL USE OF THE REPUBLIC OF SLOVENIA and corresponding to the source database entitled “Immigrants aged 15 or more by activity status, nationality, country of previous residence and sex, Slovenia, annually”.

Actual data are available in Px-Axis format (.px). With additional links, you can access the source portal page for viewing and selecting data, as well as the PX-Win program, which can be downloaded free of charge. Both allow you to select data for display, change the format of the printout, and store it in different formats, as well as view and print tables of unlimited size, as well as some basic statistical analyses and graphics.

Data on countries of citizenship by immigrant status and period of immigration, by admission category and applicant type, age and gender for the population in private households in Canada, provinces and territories, census metropolitan areas, census agglomerations and parts.

The project aims at providing the data required to study the descriptive representation of citizens of immigrant origin (CIOs). The main aim is to provide an overview of the social and political profile of Member of Parliament (MPs), with a particular focus on identifying MPs of immigrant origin. In addition to the national level dataset described below, a corresponding regional level dataset is available.

Identification variables: Political level (regional, national); country-ID (NUTS); name of region; region-id (NUTS); date of relevant election; full name of district in which elected; level of electoral tier (first / Lower (or single tier); identifier for tier 1 to 3 districts at national level; number of legislatures in the country, as recorded by the parliament itself; date in which the legislature begins and ends; first name, first (second) surname of MP; MP-ID; national MP is also simultaneously a regional MP; which regional MP.

Demography: sex of MP; year of birth of MP; highest level of education (ISCED 1997); last occupation /profession of the MP before first ever becoming an MP (ISCO 2008); occupation sector when first elected; current occupation/ profession of the MP (ISCO 2008); current occupation sector.

Electoral and parliamentary tenure variables: number of times the MP has been previously elected to parliament in this district; type of electoral district; number of times the MP has been previously elected to parliament in this tier; Rookie: MP elected for the first time in this term; number of times the MP has been elected to parliament; number of times the MP has taken up the seat in parliament once elected; year when the MP was first elected to national/regional parliament; total number of years spent in national/regional parliament as MP, prior to this legislature (seniority); when was the MP elected for the last time prior to this legislature (continuity); MP was elected to chamber from inauguration; MP stayed continuously with no interruptions from the moment of taking up the seat until the end of the legislative term; number of months the MP did serve (if he did not serve a full legislative term); MP came back to reclaim the seat if MP left seat at some point; position in party list; rank position in which the MP was elected in district; double candidacy in another tier; MP won seat as incumbent, or as contender; parliamentary group the MP joined at the beginning and at the end of his/her term; full name and acronym of party or list in which elected; party code according to the CMP (Comparative Manifesto Project) dataset; party-ID.

Immigrant origin variables (corresponding coding for MPs mother and father): MP was born in the country of parliament; country (ISO 3166-1), world region (UN Classification for ‘Composition of macro geographical regions’), and country region (NUTS) in which the MP was born; data sources for country of birth (e.g. official parliamentary source, personal blogs, etc.); specific sources for country of birth; reliability of the data regarding the country of birth of the MP (as judged by the coder); year of immigration; born as a national citizen of the country of parliament; country of nationality at birth; data sources country of nationality at birth; specific sources for country of citizenship at birth; reliability of the data regarding citizenship at birth; year in which naturalized as a citizen; data sources year of naturalization; specific sources for date of naturalization; reliability of the data regarding naturalization.

Variables relating to aspects potentially related to discrimination: the MP is a native speaker of an official country language and data sources; specific sources for native language of MP; MP can be perceived by voters as a member of an ‘identifiable’ minority; source where picture found; specific sources for picture of MP; does the MP self-identify as a member of an ethnic minority; ethnicity; sources and specific sources for information on ethnic self-identification of MP; self-identification as a member of a certain religion; religion the MP identifies with.

Party career and committee membership variables: year in which the MP joined the party for which she/he was elected in this legislative term; highest position within the party; MP changed party affiliation during the legislative term; date of change; full name and party acronym of the new party joined, CMP code of the new party and Pathways identifier for party; (corresponding coding if the MP changed party affiliation during the legislative term a second time); ever a local councilor or mayor prior to, or while, being elected an MP this legislative term; total number of years in the local council as a mayor and/or councilor; ever a member of the regional parliament prior to being elected a national MP this legislative term; number of years in the regional parliament prior to this legislature; ever a member of the European Parliament prior to being elected a...

Global matrices of bilateral migrant stocks spanning the period 1960-2000, disaggregated by gender and based primarily on the foreign-born concept are presented. Over one thousand census and population register records are combined to construct decennial matrices corresponding to the last five completed census rounds.For the first time, a comprehensive picture of bilateral global migration over the last half of the twentieth century emerges. The data reveal that the global migrant stock increased from 92 to 165 million between 1960 and 2000. South-North migration is the fastest growing component of international migration in both absolute and relative terms. The United States remains the most important migrant destination in the world, home to one fifth of the world™s migrants and the top destination for migrants from no less than sixty sending countries. Migration to Western Europe remains largely from elsewhere in Europe. The oil-rich Persian Gulf countries emerge as important destinations for migrants from the Middle East, North Africa and South and South-East Asia. Finally, although the global migrant stock is still predominantly male, the proportion of women increased noticeably between 1960 and 2000.

This Alberta Official Statistic describes the proportion of immigrants that reside in each of the eight Alberta economic regions based on the 2011 National Household Survey. Canada is a multicultural society whose ethnocultural make-up has been shaped over time by immigrants and their descendants. Each new wave of immigration has added to the nation’s ethnic and cultural composition. Over time, patterns of immigration have shifted. Historically, most immigrants came from Europe. More recently, the largest group of newcomers to Canada has come from Asia (including the Middle East).

The dataset contains annual data on the flows of international migrants as recorded by Italy. The data presents both inflows and outflows according to the place of birth, citizenship or place of previous / next residence both for foreigners and nationals.

This dataset is part of a compilation of data on international migration flows which is useful for analytical purposes, but also serves to raise awareness about the problems of comparability among available statistics. Countries collecting and publishing data on the flows of international migrants use different definitions to identify migrants and use different concepts to determine their origin and destination.

UK residents by broad country of birth and citizenship groups, broken down by UK country, local authority, unitary authority, metropolitan and London boroughs, and counties. Estimates from the Annual Population Survey.

In 2015 a team of researchers based in Greece, Italy, Turkey and Malta undertook interviews with refugees and migrants as well as stakeholders and observed events of the so-called ‘migration crisis’ as they unfolded.

The dataset deposited here includes information on semi-structured interviews with a total of 500 refugees and migrants, 440 of whom had crossed the Mediterranean by boat in 2015 to Greece (215 interviews), Italy (205 interviews) and Malta (20 interviews) together with a further 60 respondents who had moved to Turkey and were considering making the onward journey to Europe. These countries reflected the key locations of the crisis.

The initial analysis of the dataset has meant that it has been coded to record who was on the move, the journeys that they made and the routes that they took. This enables an examination of the relationship between micro-level characteristics and the geographies of migration that were recorded.

Specifically the dataset here includes:

1. Methodological note - a description of the project, the approach to the fieldwork and the analysis undertaken

2. Individuals - data on the demographic and socio-economic characteristics of the interviewees.

3. Routes - data on the routes taken by our interviewees and the duration taken to travel along them.

4. Journeys - data setting out the individual stops and journeys recorded from each interviewee, travel method between them and duration of travel. This has been prepared for insertion into GIS Mapping software.

   In the first six months of 2015 more than 100,000 migrants crossed the Mediterranean, arriving at the shores of southern Europe in search of protection or a better life. In the same period more than 1,800 people lost their lives, drowning as overloaded and often unseaworthy boats sank into the sea. Although the crisis is in many ways nothing new, these scenes have captured the public and media imagination and have challenged the ability of European States to respond appropriately. Recent months have seen increasingly heated discussions at the national and EU level about whether rescues at sea are a vital humanitarian intervention or simply encourage others to attempt the crossing, and whether those who arrive can be dealt with through mandatory or voluntary relocation quotas. Many of these discussions are underpinned by assumptions about why it is that migrants make the journey to Europe in the first place.

In this context the research aims to better understand the dynamics of migration in the Mediterranean region by providing the first large-scale, systematic and comparative study of the backgrounds, experiences, aspirations and routes of migrants in four European countries (Italy, Greece, Malta and Turkey) gathered from 550 migrants who have recently arrived and 100 stakeholders. The research pushes the theoretical and conceptual boundaries of migration studies, encouraging critical reflexive dialogue and practice by opening new and inclusive spaces for questioning and challenging established ways of categorising and thinking about with the Mediterranean migration crisis. In so doing it will create opportunities for increased policy dialogue and academic collaboration between the case study countries - and across the EU more generally - around the evidence gathered.

The research is underpinned by a number of urgent research questions which inform the collection and analysis of the data: 1. What are the underlying factors shaping migration from countries of origin and how do the characteristics and backgrounds of migrants shape the response to structural issues? 2. What are the opportunity structures that shape, inform or constrain migrant journeys to Europe? 3. What are the differences between the Central Mediterranean (principally from Libya to Italy and Malta) and Eastern (Turkey to Greece) Mediterranean routes? 4. To what extent are migrant journeys to Europe, or particular countries within Europe, shaped or even determined by non-state actors (agents, facilitators and civil society)? 5. What are the impacts of policies intended to deter or prevent migrants from crossing the Mediterranean?

The research will be delivered by a team of leading UK migration scholars from the Universities of Coventry, Oxford, Birmingham and Sussex working in collaboration with academic partners in the case study countries and supported by experts from international, governmental and non-governmental organisations. The team has established relationships with local civil society organisations that will facilitate access to research participants and provide advice and information on policy or other developments which could impact on the delivery of the project.

The research will benefit a wide range of academic, governmental, international and civil society organisations and inform the development of strategic, political and policy responses to the migration crisis in the Mediterranean. This impact will be secured through...

To what extent does exposure to immigration condition the types of immigrants citizens are willing to admit? Extending the conjoint approach adopted by Hainmueller and Hopkins (2015), this study investigates whether the admission preferences of French natives vary based on personal exposure to immigration, as proxied by local demographics and self-reported social contact. Methodologically, we propose and apply new methods to compare attribute salience across different subgroups of respondents. We find that although an inflow of immigrants into respondents' municipalities has a limited influence on how French natives evaluate prospective immigrants, social contact with immigrants matters. Specifically, French natives who do not frequently interact with immigrants are significantly less favorable toward immigrants from non-western countries, and more favorable toward immigrants from western countries. In contrast, natives who report frequent social interactions with immigrants place less weight on nationality as a criterion for immigrant admission. Although scholars have noted an increasing consensus in immigration attitudes across developed democracies, our findings suggest that individual experiences with immigration condition preferences for immigration policy at the national level.

The thirteenth of 20 years of International Social Survey Programme (ISSP) surveys in New Zealand by Professor Philip Gendall, Department of Marketing, Massey University.A verbose rundown on topics covered follows.Questions on national consciousness and national identity. Identification with the town, the city, the region, the nation and with the respective continent; most important characteristics for national identity; identification with one’s own nation and national pride (scale); perceived pride in the democracy of the country, the political influence of the country in the world, the economic achievement, the social security system, the scientific achievements, the achievements in sports, the achievements in arts or literature, the armed forces, the history and equal rights of all social groups in society.Preference for protective duty to support the national economy; attitude to the right of international institutions to enforce solutions to be accepted nationally; attitude to enforcing national interests regardless of evoking conflicts with other countries; rejection of acquisition of land by foreigners in one’s country; preference for national films in national television stations; damage done by large international companies to the local business; attitude to free trade; attitude to follow the decisions of international organisations even if the local government does not agree with them; international organisations take away too much power from the country.Availability of worldwide information as a benefit of the internet; importance of sharing national customs and traditions to achieve full nationality; attitude to government support of national minorities to preserve their customs and habits; preference for assimilation of minorities or retention of their identity; hostility to foreigners and prejudices against immigrants (scale); attitude to a reduction of immigration of foreigners; respondents citizenship; citizenship of parents at birth of respondent; birthplace or citizenship of parents should allow naturalization of children; same rights for citizens and legal immigrants; attitude towards stronger measures regarding illegal immigrants; languages spoken at home; perceived ethnic affiliation and strength of this feeling.Demography: Sex; age; marital status; steady life-partner; years in school, current employment status; current employment status of spouse; hours worked weekly; occupation of respondent and spouse (ISCO-88); respondent and spouse working for private, public sector or self-employed; supervisor function; union membership; household size; family income; respondents earnings; household composition; self-placement on a left-right continuum; party preference; vote last election; religious denomination; frequency of church attendance; self-placement on a top-bottom scale; region; town size, rural or urban region; ethnicity or nationality. Additionally encoded: Mode of data collection.

This data set is about ICE detains noncitizens as necessary, most noncitizens subject to removal are monitored outside the detention setting through a variety of mechanisms. Cases on the non-detained national docket are either categorized as “Final Order,” meaning the noncitizen has completed the legal process and has been ordered removed, or “Pending Final Order,” indicating that an order of removal has not yet been issued or is not administratively final.

The twenty most common countries of origin for immigrants and mother’s origin for native descendants, with proportional share in the population from the country, and share of students on the specialisation tracks natural science (N); language, social science and economy (S); and other (O), respectively. The total is the summed share from the twenty most common countries, and shares in the whole set of immigrants and descendants, respectively, on the respective specialisation tracks. Note that school classes with too few immigrants to perform our analyses have been excluded. Including the whole population, not only those in our analysis, would increase the figures for “other” specialisations. All figures are in percent.

Italy is one of the most representative ‘new immigration countries’. Between the 1980s and the 1990s, it became a major country of destination for immigrants coming from Asia, Middle East and North Africa. As a result, since the mid-nineties, immigration has gained salience within the Italian political debate. Building on the existing literature on agenda-setting and framing studies, this article studies the evolution of the immigration issue in Italy over the last two decades. It focuses on the framing and, more specifically, the position political actors tend to adopt when debating on immigration. In particular, the main research questions are: to what extent is the framing of immigration associated with the traditional left vs. right spectrum? Do incumbent political parties tend to adopt a different position toward immigration than opposition parties? This article analyses party competition dynamics over the immigration issue in Italy from 1995 to 2011. The author carried out a political-claim analysis of articles from two Italian national daily newspapers. Findings show that immigration is more a positional issue than a valence one. Political actors’ positions towards migration appear to be anchored to the old left vs. right dimension of the political conflict. This demonstrates that parties’ engagement within the political conflict goes beyond electoral campaigns. Finally, being in government seems to play a crucial role in “softening” the way party actors frame immigration, in terms of both the arguments used and the pro- or anti-immigration positions adopted.

People who have been granted permanent resident status in Canada. Please note that in these datasets, the figures have been suppressed or rounded to prevent the identification of individuals when the datasets are compiled and compared with other publicly available statistics. Values between 0 and 5 are shown as “--“ and all other values are rounded to the nearest multiple of 5. This may result to the sum of the figures not equating to the totals indicated.