The estimated population of all ages in Yukon amounted to ****** people in 2024. Between 1971 and 2024, the estimated population rose by ****** people, though the increase followed an uneven trajectory rather than a consistent upward trend.

Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

This statistic shows the population distribution of Yukon, Canada in 2016, by urban/rural type. In 2016, 39.4 percent of Yukon's population lived in rural areas.

This table contains 13 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2000-02-18. This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia ...).

Statistics Canada's 2021 Census data regarding the total population in private households by religion. Statistics Canada. 2022. Census Profile. 2021 Census of Population. Statistics Canada Catalogue number 98-316-X2021001. Ottawa. Released October 26, 2022. https://www12.statcan.gc.ca/census-recensement/2021/dp-pd/prof/index.cfm

The Atlas of Canada 1,000,000 National Frameworks data are a set of integrated base map layers which form the Atlas of Canada 1,000,000 National Frameworks Data collection. These data have been compiled at a scale of 1:1,000,000 with the primary goal being to indicate correct relative positioning with other frameworks layers rather than absolute positional accuracy.

The number of deaths in Yukon stood at 328 people in 2023. Between 1971 and 2023, the deaths rose by 224 people, though the increase followed an uneven trajectory rather than a consistent upward trend.

Statistics Canada's 2011 National Household Survey data regarding population groups who identify with Indigenous peoples of Canada. Statistics Canada. 2013. National Household Survey Profile. 2011 National Household Survey. Statistics Canada Catalogue no. 99-004-XWE. Ottawa. Released September 11 2013. https://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/index.cfm?Lang=E

Canada, with 3.3 people per square kilometre, has one of the lowest population densities in the world. In 2001, most of Canada's population of 30 million lived within 200 kilometres of the United States. In fact, the inhabitants of our three biggest cities — Toronto, Montréal and Vancouver — can drive to the border in less than two hours. Thousands of kilometres to the north, our polar region — the Yukon Territory, the Northwest Territories and Nunavut — is relatively empty, embracing 41% of our land mass but only 0.3% of our population. Human habitation in the solitary north clings largely to scattered settlements: villages among vast expanses of virgin ice, snow, tundra and taiga.

Housing Assessment Resource Tools (HART) This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories - All 43 census metropolitan areas (CMAs) in Canada Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Universe: Full Universe: Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings. Definition of Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Table 1: Age / Gender (12) 1. Total – Population 55 years and over 2. Men+ 3. Women+ 4. 55 to 64 years 5. Men+ 6. Women+ 7. 65+ years 8. Men+ 9. Women+ 10. 85+ 11. Men+ 12. Women+ Housing indicators (13) 1. Total – Private Households by core housing need status 2. Households below one standard only...

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map consisting of two condensed maps showing the distribution of rural population according to the 1951 census of Canada. The term 'rural population' embraces all persons residing outside the census metropolitan areas and cities, towns and villages of 1000 inhabitants and over, whether such cities, towns and villages were incorporated or not. The distribution is shown according to the two divisions of rural population commonly made, namely, rural farm and rural non-farm. The rural farm population comprises all people residing on a farm regardless of occupation. A farm for such purposes is defined as a land holding of over three acres in size on which agricultural operations are carried out, or a land holding from one to three acres in size, which in 1950 accounted for an agricultural production amounting to $250 or more. All other persons classed as rural population come under the rural non-farm division. The northern parts of Yukon Territory and the Northwest Territories are not included on the rural non-farm map although there are some rural non-farm dwellers in these areas. In 1951, Canada's rural population was 52.5% rural farm, and 47.5% rural non-farm.

Statistics Canada's 2021 Census data regarding population groups who identify with Indigenous peoples of Canada.Keywords: First nation, Indigenous, Métis, Inuk, Inuit, Ancestry Statistics Canada. 2022. Census Profile. 2021 Census of Population. Statistics Canada Catalogue number 98-316-X2021001. Ottawa. Released October 26, 2022. https://www12.statcan.gc.ca/census-recensement/2021/dp-pd/prof/index.cfm

Tabular data for lynx captures used in analyses related to Derek Arnold's Ph.D. dissertation, 'Movement ecology, survival, and territorial dynamics in Canada lynx (Lynx canadensis) over a cyclic population decline'. These data are a subset of the capture data for the 'Movement Patterns, Dispersal Behavior, and Survival of Lynx in Relation to Snowshoe Hare Abundance in the Boreal Forest' project sponsored by the U.S. Fish and Wildlife Service.

The ZIP file contains the following files:1_hare_CMR_data_20251008_FINAL: Capture-mark-recapture data file that contains all information needed to fit multi-state capture-mark-recapture models.2_hare_CMR_code_20251008_FINAL.R: This script file reads the data files, and fits multi-state capture-mark-recapture models.3_hare_all_vital_rates_20251008_FINAL.rda: State-specific vital rates data that are needed to perform matrix model analyses.4_sensitivity and elasticity results_20251008_FINAL.csv: A CSV data file containing data on point estimates of state-specific vital rates, and sensitivity and elasticity of population growth rate to lower-level vital rates for each season and phase of the cycle.5_hare_MM_code_20251008_FINAL.R: R script to read vital rate data, and perform matrix model analyses.6_hare_MM_analysis_functions_20251008_FINAL.R: A R file containing functions sourced by 5_hare_MM_code_20251008_FINAL.R to perform standard matrix model analyses, and lower-level LTRE analyses.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

POSTAL

1,487 named individuals were selected from the Karom Group of Companies, Dialogue Canada household mail panel. This mail panel includes a cross-section of Canadians, with the exception of those living in the Yukon, Northwest Territories or Nunavut, from which a sample can be obtained to represent the Canadian population according to the most recent Statistics Canada data. The panel file was stratified by regions in Canada: city size, French Quebec and rest of Canada and ordered by postcode. The 1,487 named individuals were selected from the Dialogue Mail panel file, using a random method on the sample sorted by postcode.

Individual members of each household who were asked to complete the survey were identified by birth date and gender with this identifying information.

From the initial 1,487 mailed out, 816 questionnaires came back hence reaching a response rate of 55%.

CATI

The sample was drawn in such a way that it represented the Canadian population with the exception of the Canadians living in the Yukon, Northwest Territories or Nunavut.

The sampling model relied on the stratification of the population by ten provinces and by six community sizes. Telephone numbers were selected from the most recently published telephone directories. These numbers acted as "seeds" from which the sample was actually generated. The original "seed" telephone numbers were not used in the sample. Both unlisted numbers and numbers listed after the directory publication are included in the sample.

From within each household contacted, respondents 18 years of age and older were screened for random selection using the most recent birthday method.

From the 12,350 total calls made, 778 calls completed the interview. Among the 12,350 calls, 8,466 were ineligibles and from the latter, 5,305 calls for which the respondent was unavailable. The net response rate is therefore 24.6%.

Mode of data collection

Mail Questionnaire [mail]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

Age, sex and length data provide population dynamics information that can indicate how populations trends occur and may be changing. These data can help researchers estimate population growth rates, age-class distribution and population demographics. Knowing population demographics, growth rates and trends is particularly valuable to fisheries managers who must perform population assessments to inform management decisions. These data are therefore particularly important in valuable fisheries like the salmon fisheries of Alaska.

This dataset includes age, sex and length data compiled from annual sampling of commercial and subsistence salmon harvests and research projects in the Yukon and Kuskokwim Management Areas. It includes data collected from 1960-2016 on five salmon species: Chinook, Chum, Coho, Pink and Sockeye. Age estimates were made by examining scales or bony structures (eg. Otoliths - ear bones). Scales were removed from the side of the fish; usually the left side above the lateral line. Scales or bony structures were then mounted on gummed cards and pressed on acetate to make an impression. The number of freshwater and saltwater annuli (ie. rings) was counted to estimate age in years. Age is recorded in European Notation, which is a method of recording both fresh and saltwater annuli. For example, for a fish that spent one year in freshwater and 3 years in saltwater, its age is recorded as 1.3. The total fish age is the sum of the first and second numbers, plus one to account for the time between deposition and emergence. Therefore the fish in this example is 5 years old. Fish sex was determined by either examining external morphology (eg. head and belly shape) or internal sex organs. Length was measured in millimeters, generally from mid-eye to the fork of the tail.

Datasource: Statistics Canada. 2012. Census Profile - Age, Sex, Marital Status, Families, Households, Dwellings and Language for Canada, Provinces, Territories, Census Divisions and Census Subdivisions, 2011 Census. Statistics Canada Catalogue http://www12.statcan.gc.ca/census-recensement/2011/dp-pd/prof/details/pa... 98-314-XCB2011006 Ottawa. Accessed November 23, 2012. Statistics Canada. 2012. 2011 Semi-custom Profile of Yukon Territory and Selected Regions, 2011 Census. CRO0130687_SP.1. Ottawa. November 20, 2012. Footnotes: A value of 0 in any given cell represents one of the following: 1) value is actually zero; 2) value may be random rounded to zero; or 3) value is more than zero but is suppressed for confidentiality reasons. This table is based on . Values have been subjected to a confidentiality procedure known as random rounding. For Statistics Canada's definition of terms, http://www12.statcan.ca/english/census06/reference/dictionary/atoz.cfm.

Number of potential territories, number of cackling Canada Goose nests, and percent occupancy of available territories from CCG plots on the Yukon Delta National Wildlife Refuge in 1982 and 1983. Also presented nesting trend data from 1960 to 1983.

During June, we perform ground-based composition counts to estimate calf production, recruitment, and adult sex ratio. We have radiocollared over 100 muskoxen in order to document seasonal shifts in distribution and habitat use, and to estimate survival and cause-specific mortality. Following the 1969 release, muskoxen increased rapidly in the Arctic Refuge, reaching a peak of approximately 400 individuals in 1986. This was followed by expansion of the population’s range into contiguous areas of north-central Alaska and northwestern Canada. We subsequently implemented cooperative surveys with the Alaska Department of Fish and Game (ADFG), Parks Canada, and Yukon Department of Environment to monitor the entire population. The number of muskoxen within the Refuge declined slightly, and then remained stable at about 325 from 1987 to 1998. We observed a precipitous decline in abundance of muskoxen within the Arctic Refuge beginning in 1999. In 2003, we estimated that fewer than 50 muskoxen occurred within Refuge boundaries. We attribute this decline to shifts in distribution, low calf recruitment, and decreased adult survival. In a recent cooperative study with ADFG (Reynolds et al. 2002), we determined that predation by grizzly bears was a significant and increasing source of mortality for muskoxen. The negative effect of predation on survival may be exacerbated by environmental conditions that limit access to forage, such as icing events and deep, persistent snows. We are continuing to monitor the status of this muskox population and investigate factors responsible for observed trends.

This statistic shows the number of MRI units per million population in Canada in 2019/2020, by province. In that year, Yukon had **** MRI units per every million of its population, which was the highest figure amongst all provinces and territories.