Retail Commodity Survey: CVs for Total Sales (July 2026)

Retail Commodity Survey: CVs for Total Sales (July 2026)
Table summary
This table displays the results of Retail Commodity Survey: CVs for Total Sales (June 2026). The information is grouped by NAPCS-CANADA (appearing as row headers), and Month (appearing as column headers).

NAPCS-CANADA

Month

202606

202607

Total commodities, retail trade commissions and miscellaneous services

0.63

0.60

Retail Services (except commissions) [561]

0.63

0.61

Food and beverages at retail [56111]

1.65

1.54

Cannabis products, at retail [56113]

0.00

0.00

Clothing at retail [56121]

0.70

1.05

Jewellery and watches, luggage and briefcases, at retail [56123]

3.63

3.31

Footwear at retail [56124]

1.11

1.07

Home furniture, furnishings, housewares, appliances and electronics, at retail [56131]

0.83

0.71

Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141]

2.52

2.69

Publications at retail [56142]

8.32

9.86

Audio and video recordings, and game software, at retail [56143]

4.22

9.28

Motor vehicles at retail [56151]

1.58

1.50

Recreational vehicles at retail [56152]

4.10

3.85

Motor vehicle parts, accessories and supplies, at retail [56153]

1.47

1.52

Automotive and household fuels, at retail [56161]

1.35

1.26

Home health products at retail [56171]

2.59

2.60

Infant care, personal and beauty products, at retail [56172]

3.59

3.00

Hardware, tools, renovation and lawn and garden products, at retail [56181]

1.96

1.94

Miscellaneous products at retail [56191]

3.48

3.27

Retail trade commissions [562]

1.58

1.58

Retail Commodity Survey: CVs for Total Sales (Second Quarter 2026)

Retail Commodity Survey: CVs for Total Sales (Second Quarter 2026)
Table summary
This table displays the results of Retail Commodity Survey: CVs for Total Sales (Second Quarter 2026). The information is grouped by NAPCS-CANADA (appearing as row headers), and Quarter (appearing as column headers).

NAPCS-CANADA

Quarter

2026Q2

Total commodities, retail trade commissions and miscellaneous services

0.47

Retail Services (except commissions) [561]

0.47

Food and beverages at retail [56111]

0.65

Cannabis products, at retail [56113]

0.00

Clothing at retail [56121]

0.66

Jewellery and watches, luggage and briefcases, at retail [56123]

2.86

Footwear at retail [56124]

1.01

Home furniture, furnishings, housewares, appliances and electronics, at retail [56131]

0.77

Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141]

2.47

Publications at retail [56142]

7.66

Audio and video recordings, and game software, at retail [56143]

5.67

Motor vehicles at retail [56151]

1.30

Recreational vehicles at retail [56152]

2.67

Motor vehicle parts, accessories and supplies, at retail [56153]

1.23

Automotive and household fuels, at retail [56161]

1.27

Home health products at retail [56171]

2.67

Infant care, personal and beauty products, at retail [56172]

3.81

Hardware, tools, renovation and lawn and garden products, at retail [56181]

1.77

Miscellaneous products at retail [56191]

3.30

Retail trade commissions [562]

1.43

Archived - Evaluation of the Canadian Centre for Justice Statistics Program - Information Sheet

Evaluation of the Canadian Centre for Justice Statistics Program - Information Sheet
Description - Evaluation of the Canadian Centre for Justice Statistics Program - Information Sheet

1: About the evaluation

Statistics Canada evaluates programs like the Canadian Centre for Justice Statistics (CCJS) to assess their relevance and performance. The evaluation of the CCJS covered the period from 2011/2012 to 2015/2016 and program expenditures of $40.7 million.

The evaluation was conducted in accordance with the Treasury Board of Canada Policy on Evaluation (2009). It provides a neutral assessment of the relevance and performance of the CCJS based on evidence gathered through a document and literature review, a survey of users, key informant interviews, and other data.

A yellow ribbon crosses the page with the text: "Police Line Do Not Cross"

A magnifying glass appears on the yellow ribbon with the text: $40.7 M in program expenditures

2: About the CCJS

The mandate of the CCJS is to provide information to the justice community and the public on the nature and extent of crime and on the administration of criminal and civil justice in Canada.

CCJS survey topics include

  • police-reported crime
  • homicide
  • police administration
  • adult and youth criminal courts and corrections
  • expenditures and personnel for civil courts and adult corrections.

3: We learned that the CCJS…

  • aligns with the Government of Canada's current priorities and is responsive to the ongoing needs of a wide range of users.
  • provides statistical information that is accessible, accurate, interpretable, relevant and released according to established schedules.
  • remains committed to offering quality crime and justice outputs that meet overall needs and priorities.
  • offers accessibility and quality of customized information and support services to its stakeholders, who are satisfied with them.

4: Satisfaction with CCJS

Statistics Canada uses six dimensions to evaluate the quality and fitness for use of its statistical information. CCJS survey respondents were asked to rate their level of satisfaction with these quality dimensions.

  • CCJS overall: 94% of satisfied respondents
  • Data accuracy: 94% of satisfied respondents
  • Data coherence: 94% of satisfied respondents
  • Data interpretability: 88% of satisfied respondents
  • Data accessibility (website): 88% of satisfied respondents
  • Data timeliness: 74% of satisfied respondents
  • Relevance - coverage of issues of most importance: 49% of respondents who said completely or to a great extent and 47% of respondents who said to some extent
  • Relevance - responsiveness to emerging trends: 20% of respondents who said completely or to a great extent and 64% of respondents who said to some extent

A yellow ribbon crosses the page with the text: "Police Line Do Not Cross"

5: How can we improve the CCJS?

  • Explore the possibility of producing more timely indicators in key selected areas with input from partners to provide earlier indications of issues and trends.
  • Establish an appropriate mechanism through which academia can be part of formal consultations.
  • Explore communication vehicles to promote awareness of CCJS data among the research and academia community.

Management agreed with the evaluation recommendations and proposed an action plan to address them.

Source: Evaluation of the Canadian Centre for Justice Statistics Program (2011/2012 to 2015/2016).

2026 Field Crop Survey - November

Introduction

Purpose

The purpose of the field crop surveys is to obtain information on seeded and harvested field crop areas, average yields, production and on-farm stocks at strategic times over the course of a typical crop cycle, which ranges from spring to late fall. Therefore, the field crop surveys are conducted in June, November and December. Model-based estimates are used for March on-farm stocks and model-based estimates of yields and production, obtained from satellite imagery, are produced in July and August. Seeding intentions are collected in December.

Additional information

Your information may also be used by Statistics Canada for other statistical and research purposes.

Authority

This information is collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.

Completion of this questionnaire is a legal requirement under this act.

Purpose

The purpose of the field crop surveys is to obtain information on seeded and harvested field crop areas, average yields, production and on-farm stocks at strategic times over the course of a typical crop cycle, which ranges from spring to late fall. Therefore, the field crop surveys are conducted in June, November and December. Your information may also be used by Statistics Canada for other statistical and research purposes.

Confidentiality

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent, or as permitted by the Statistics Act. Statistics Canada will use the information from this survey for statistical purposes only.

Data-sharing agreements

To reduce respondent burden, Statistics Canada has entered into data-sharing agreements with provincial and territorial statistical agencies and other government organizations, which have agreed to keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.

Section 11 of the Statistics Act provides for the sharing of information with provincial and territorial statistical agencies that meet certain conditions. These agencies must have the legislative authority to collect the same information, on a mandatory basis, and the legislation must provide substantially the same provisions for confidentiality and penalties for disclosure of confidential information as the Statistics Act. Because these agencies have the legal authority to compel businesses to provide the same information, consent is not requested and businesses may not object to the sharing of the data.

For this survey, there are Section 11 agreements with the provincial statistical agencies of Newfoundland and Labrador, Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta and British Columbia. The shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province.

Section 12 of the Statistics Act provides for the sharing of information with federal, provincial or territorial government organizations. Under Section 12, you may refuse to share your information with any of these organizations by writing a letter of objection to the Chief Statistician and returning it with the completed questionnaire. Please specify the organizations with which you do not want to share your data.

For this survey, there are Section 12 agreements with provincial and territorial ministries of agriculture and with the Prince Edward Island Statistical agency.

For agreements with provincial and territorial government organizations, the shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory.

Record linkage

To enhance the data from this survey and to minimize the reporting burden, Statistics Canada may combine it with information from other surveys or from administrative sources.

Security of emails and faxes

Statistics Canada advises you that there could be a risk of disclosure during facsimile or email. However upon receipt, Statistics Canada will provide the guaranteed level of protection afforded all information collected under the authority of the Statistics Act.

Note: Our online questionnaires are secure, there is no risk of data interception when responding to Statistics Canada online surveys.

Reporting instructions

Business or organization and contact information

1. Please verify or provide the business or organization's legal and operating name and correct where needed. Note: Legal name modifications should only be done to correct a spelling error or typo.

  • Legal name
  • Operating name (if applicable)

2. Please verify or provide the contact information of the designated business or organization contact person for this questionnaire and correct where needed.

Note: The designated contact person is the person who should receive this questionnaire. The designated contact person may not always be the one who actually completes the questionnaire.

  • First name
  • Last name
  • Title
  • Preferred language of communication
  • Mailing address (number and street)
  • City
  • Province, territory or state
  • Postal code or ZIP code
  • Country
  • Email address
  • Telephone number (including area code)
  • Extension number (if applicable)
  • Fax number (including area code)

3. Please verify or provide the current operational status of the business or organization identified by the legal and operating name above.

  1. Operational
  2. Not currently operational e.g., temporarily or permanently closed, change of ownership
    • Why is this business or organization not currently operational?
      1. Seasonal operations
      2. Ceased operations
      3. Sold operations
      4. Amalgamated with (an) other business(es) or organization(s)
      5. Temporarily inactive but will re-open
      6. No longer operating due to other reason(s)
    • Business or organization and contact information - Question identifier: 3a
      • Seasonal operations
      • When did this business or organization close for the season?
        Date:
      • When does this business or organization expect to resume operations?
        Date:
    • Business or organization and contact information - Question identifier: 3b
      • Ceased operations
        • When did this business or organization cease operations?
          Date:
        • Why did this business or organization cease operations?
          1. Bankruptcy
          2. Liquidation
          3. Dissolution
          4. Other reasons - specify: 
        • Why did this business or organization cease operations?
          Other reasons - specify:
    • Business or organization and contact information - Question identifier: 3c
      • Sold operations
        • When was this business or organization sold?
          Date:
        • What is the legal name of the buyer?
    • Business or organization and contact information - Question identifier: 3d
      • Amalgamated with (an) other business(es) or organization(s)
        • When did this business or organization amalgamate?
          Date:
        • What is the legal name of the resulting or continuing business or organization?
        • What is (are) the legal name(s) of the other amalgamated business(es) or organization(s)?
    • Business or organization and contact information - Question identifier: 3e
      • Temporarily inactive but will re-open
        • When did this business or organization become temporarily inactive?
          Date:
        • When does this business or organization expect to resume operations?
          Date:
        • Why is this business or organization temporarily inactive?
    • Business or organization and contact information - Question identifier: 3f
      • No longer operating due to other reason(s)
        • When did this business or organization cease operations?
          Date:
        • Why did this business or organization cease operations?

Main activity

4. Please verify or provide the current main activity of the business or organization identified by the legal and operating name.

Note: The described activity was assigned using the North American Industry Classification System (NAICS).

  1. This is the current main activity. - Go to next section
  2. This is not the current main activity.
    Please provide a brief but precise description of this business or organization's main activity.
    e.g., breakfast cereal manufacturing, shoe store, software development

5. Was this business or organization's main activity ever classified as:

  1. Yes
  2. No - Go to next section

6. When did the main activity change?

Date:

All land operated

The following questions deal with all land operated.

Include land rented from other operations and Crown or public land used for agricultural purposes.
Exclude land rented to other operations.

Unit of measure

1. For the following questions, what unit of measure will be used to report land areas?

  1. Acres
  2. Hectares
  3. Arpents (for Québec only)

Fall rye and winter wheat seeded in previous year

2. In the fall of 2025, did you seed any fall rye and/or winter wheat?

  1. Yes - Go to question 3
  2. No - Go to question 7

3. For the following crops, indicate the area seeded in the fall of 2025 and the area harvested as grain.

  1. Fall rye
  2. Winter wheat

4. For the harvested area of fall rye and winter wheat, do you prefer to report the average yield or the total production?

  1. Average yield - Go to question 5
  2. Total production - Go to question 6

5. For the fall rye and winter wheat, indicate the average yield you obtained in 2026.

Go to question 7

6. For the fall rye and winter wheat, indicate the total production you obtained in 2026.

Total production: Unit of measure
(select per crop)

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights
    1. Fall rye
    2. Winter wheat

Fall rye and winter wheat seeded this year

7. Did you or do you intend to seed any fall rye or winter wheat in the fall of 2026?

  1. Yes - Go to question 8
  2. No - Go to question 9

8. For the fall rye and/or winter wheat, what is the area you seeded or intend to seed in the fall of 2026?

  1. Fall rye
  2. Winter wheat

Crops seeded 2026

9. Did you seed any crops in 2026?

  1. Yes - Go to question 10
  2. No - Go to question 30

Areas seeded and harvested in 2026

10. For the following crops, what is the seeded area and the area harvested or expected to be harvested as grain in 2026?

Area harvested or expected to be harvested as grain excludes areas of crops to be baled, used for green feed, lost to natural causes (e.g., flooding) or abandoned (due to poor quality).

  1. Barley
  2. Buckwheat
  3. Canary seed, hairless (canario)
  4. Canary seed, regular
  5. Canola (rapeseed)
  6. Chickpeas, desi
  7. Chickpeas, kabuli
  8. Chickpeas, other and unknown
  9. Corn for grain
    Include seed corn.
    Exclude sweet corn and corn for silage.
  10. Corn for silage
  11. Dry beans, black - black turtle, preto
  12. Dry beans, cranberry - romano
  13. Dry beans, dark red kidney
  14. Dry beans, great northern
  15. Dry beans, light red kidney
  16. Dry beans, pinto
  17. Dry beans, small red (red Mexican)
  18. Dry beans, white pea (Navy)
  19. Dry beans, other and unknown
  20. Dry field peas - green
    Exclude green peas for processing or fresh market
  21. Dry field peas - yellow
  22. Dry field peas - other and unknown
  23. Faba beans (fava, broad)
  24. Flaxseed
  25. Hemp
  26. Lentils - large green
  27. Lentils - red
  28. Lentils - small green
  29. Lentils - other and unknown
  30. Mixed grains 
    i.e., two or more grains sown together
  31. Mustard seed - brown
  32. Mustard seed - oriental
  33. Mustard seed - yellow
  34. Mustard seed - other and unknown
  35. Oats
  36. Potatoes
  37. Soybeans
  38. Spring rye
  39. Sugar beets
  40. Sunflower seed
  41. Triticale
  42. Tobacco
  43. Wheat, durum
  44. Wheat, spring - Canada Western Red Spring (CWRS)
  45. Wheat, spring - Canada Northern Hard Red (CNHR)
  46. Wheat, spring - Canada Prairie Spring Red (CPSR)
    Include semi-dwarf varieties
  47. Wheat, spring - Canada Prairie Spring White (CPSW)
    Include semi-dwarf varieties.
    Exclude soft white spring wheat.
  48. Wheat, spring - Canada Western Extra Strong (CWES)
    Include utility.
  49. Wheat, spring - Canada Western Hard White Spring (CWHWS)
  50. Wheat, spring - Canada Western Soft White Spring (CWSWS)
  51. Wheat, spring — Canada Eastern Red Spring (CERS)
    Include Eastern Hard Red spring
  52. Wheat, spring - other
    Include all other varieties not listed above.
  53. Other - Specify other field crops
    Exclude:
    • Alfalfa, hay and forage seed. These crops will be reported later in the questionnaire.
    • Vegetables, such as pumpkins, green peas, onions, cucumbers, tomatoes, etc.

Average yields or total production in 2026

11. For the crop(s) seeded in 2026 (excluding corn for silage), do you prefer to report the average yield or the total production?

  1. Average yield - Go to question 12
  2. Total production - Go to question 13

12. For the following crops, what is the average yield you obtained or expect to obtain in 2026?

Average yield: Unit of measure per acre, hectare or arpent as selected in question 1
(select per crop)

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights
    per acre / per hectare / per arpent

 

  1. Barley
  2. Buckwheat
  3. Canary seed, hairless (canario)
  4. Canary seed, regular
  5. Canola (rapeseed)
  6. Chickpeas, desi
  7. Chickpeas, kabuli
  8. Chickpeas, other and unknown
  9. Corn for grain
    Include seed corn.
    Exclude sweet corn and corn for silage.
  10. Corn for silage
  11. Dry beans, black - black turtle, preto
  12. Dry beans, cranberry - romano
  13. Dry beans, dark red kidney
  14. Dry beans, great northern
  15. Dry beans, light red kidney
  16. Dry beans, pinto
  17. Dry beans, small red (red Mexican)
  18. Dry beans, white pea (Navy)
  19. Dry beans, other and unknown
  20. Dry field peas - green
    Exclude green peas for processing or fresh market
  21. Dry field peas - yellow
  22. Dry field peas - other and unknown
  23. Faba beans (fava, broad)
  24. Flaxseed
  25. Hemp
  26. Lentils - large green
  27. Lentils - red
  28. Lentils - small green
  29. Lentils - other and unknown
  30. Mixed grains 
    i.e., two or more grains sown together
  31. Mustard seed - brown
  32. Mustard seed - oriental
  33. Mustard seed - yellow
  34. Mustard seed - other and unknown
  35. Oats
  36. Potatoes
  37. Soybeans
  38. Spring rye
  39. Sugar beets
  40. Sunflower seed
  41. Triticale
  42. Tobacco
  43. Wheat, durum
  44. Wheat, spring - Canada Western Red Spring (CWRS)
  45. Wheat, spring - Canada Northern Hard Red (CNHR)
  46. Wheat, spring - Canada Prairie Spring Red (CPSR)
    Include semi-dwarf varieties
  47. Wheat, spring - Canada Prairie Spring White (CPSW)
    Include semi-dwarf varieties.
    Exclude soft white spring wheat.
  48. Wheat, spring - Canada Western Extra Strong (CWES)
    Include utility.
  49. Wheat, spring - Canada Western Hard White Spring (CWHWS)
  50. Wheat, spring - Canada Western Soft White Spring (CWSWS)
  51. Wheat, spring — Canada Eastern Red Spring (CERS)
    Include Eastern Hard Red spring
  52. Wheat, spring - other
    Include all other varieties not listed above.
  53. Other - Specify other field crops
    Exclude:
    • Alfalfa, hay and forage seed. These crops will be reported later in the questionnaire.
    • Vegetables, such as pumpkins, green peas, onions, cucumbers, tomatoes, etc.

Go to question 14

13. For the following crops, what is the total production you obtained or expect to obtain in 2026?

Total production: Unit of measure
(select per crop)

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights

 

  1. Barley
  2. Buckwheat
  3. Canary seed, hairless (canario)
  4. Canary seed, regular
  5. Canola (rapeseed)
  6. Chickpeas, desi
  7. Chickpeas, kabuli
  8. Chickpeas, other and unknown
  9. Corn for grain
    Include seed corn.
    Exclude sweet corn and corn for silage.
  10. Corn for silage
  11. Dry beans, black - black turtle, preto
  12. Dry beans, cranberry - romano
  13. Dry beans, dark red kidney
  14. Dry beans, great northern
  15. Dry beans, light red kidney
  16. Dry beans, pinto
  17. Dry beans, small red (red Mexican)
  18. Dry beans, white pea (Navy)
  19. Dry beans, other and unknown
  20. Dry field peas - green
    Exclude green peas for processing or fresh market
  21. Dry field peas - yellow
  22. Dry field peas - other and unknown
  23. Faba beans (fava, broad)
  24. Flaxseed
  25. Hemp
  26. Lentils - large green
  27. Lentils - red
  28. Lentils - small green
  29. Lentils - other and unknown
  30. Mixed grains 
    i.e., two or more grains sown together
  31. Mustard seed - brown
  32. Mustard seed - oriental
  33. Mustard seed - yellow
  34. Mustard seed - other and unknown
  35. Oats
  36. Potatoes
  37. Soybeans
  38. Spring rye
  39. Sugar beets
  40. Sunflower seed
  41. Triticale
  42. Tobacco
  43. Wheat, durum
  44. Wheat, spring - Canada Western Red Spring (CWRS)
  45. Wheat, spring - Canada Northern Hard Red (CNHR)
  46. Wheat, spring - Canada Prairie Spring Red (CPSR)
    Include semi-dwarf varieties
  47. Wheat, spring - Canada Prairie Spring White (CPSW)
    Include semi-dwarf varieties.
    Exclude soft white spring wheat.
  48. Wheat, spring - Canada Western Extra Strong (CWES)
    Include utility.
  49. Wheat, spring - Canada Western Hard White Spring (CWHWS)
  50. Wheat, spring - Canada Western Soft White Spring (CWSWS)
  51. Wheat, spring — Canada Eastern Red Spring (CERS)
    Include Eastern Hard Red spring
  52. Wheat, spring - other
    Include all other varieties not listed above.
  53. Other - Specify other field crops
    Exclude:
    • Alfalfa, hay and forage seed. These crops will be reported later in the questionnaire.
    • Vegetables, such as pumpkins, green peas, onions, cucumbers, tomatoes, etc.

If corn for silage was reported in question 10, go to question 14, otherwise, go to question 18.

14. For the corn for silage seeded in 2026, do you prefer to report the average yield or the total production?

  1. Average yield - Go to question 15
  2. Total production - bushels, metric tonnes, etc. - Go to question 16
  3. Total production - using silo dimensions - Go to question 17

If corn for silage was reported in question 10, go to question 14, otherwise, go to question 18.

15. For the corn for silage, what is the average yield you obtained or expect to obtain in 2026?

Average yield: Unit of measure per acre, hectare or arpent as selected in question 1

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights
    per acre / per hectare / per arpent
    1. Corn for silage

Go to question 18

If corn for silage was reported in question 10, go to question 14, otherwise, go to question 18.

16. For the corn for silage, what is the total production you obtained or expect to obtain in 2026?

Total production: Unit of measure

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights
    1. Corn for silage

Go to question 18

Silo storage for corn for silage

17. What are the silos dimensions and percentage filled for the corn for silage stored in vertical and/or horizontal silos and/or in silo bags?

1 metre = 3 feet approximately

Vertical silos: Diameter (in feet) / Height (in feet) / % full

  1. Silo 1
  2. Silo 2
  3. Silo 3

Horizontal silos: Length (in feet) / Width (in feet) / Height (in feet) / % full

  1. Silo 1
  2. Silo 2
  3. Silo 3

Silos bags: Diameter (in feet) / Length (in feet)

  1. Silo 1
  2. Silo 2
  3. Silo 3

Percentage moisture of harvested corn

18. What is the percent moisture content of the corn for grain when harvested, if applicable?

Include seed corn.
Exclude sweet corn and corn silage.

Percentage from 1.0% to 40.0%

19. What is the percent moisture content of the corn for silage when harvested, if applicable?

Percentage from 45.0% to 90.0%

Areas with genetically modified seed (corn for grain)

If corn for grain was reported in question 10, go to question 20, otherwise, go to question 25.

20. Of the corn for grain area reported in question 10, was any seeded with genetically modified seed?

Exclude varieties produced by traditional cross-breeding techniques.

21. Of the area you reported in question 10, how much of it was seeded and harvested with genetically modified seed?

  1. Genetically modified corn for grain
    Area seeded
  2. Genetically modified corn for grain
    Area harvested or expected to be harvested as grain

22. For the genetically modified corn for grain, do you prefer to report the average yield or the total production?

  1. Average yield - Go to question 23
  2. Total production - Go to question 24

23. For the genetically modified corn for grain, what is the average yield you obtained or expect to obtain in 2026?

Go to question 25

24. For the genetically modified corn for grain, what is the total production you obtained or expect to obtain in 2026?

Areas with genetically modified seed (soybeans)

If soybeans were reported in question 10, go to question 25, otherwise, go to question 30.

25. Of the soybeans area reported in question 10, was any seeded with genetically modified seed?

Exclude varieties produced by traditional cross-breeding techniques.

26. Of the area you reported in question 10, how much of it was seeded and harvested with genetically modified seed?

  1. Genetically modified soybeans
    Area seeded
  2. Genetically modified soybeans
    Area harvested or expected to be harvested as grain

27. For the genetically modified soybeans, do you prefer to report the average yield or the total production?

28. For the genetically modified soybeans, what is the average yield you obtained or expect to obtain in 2026?

Average yield: Unit of measure per acre, hectare or arpent as selected in question 1

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights
    per acre / per hectare / per arpent 

Go to question 30

29. For the genetically modified soybeans, what is the total production you obtained or expect to obtain in 2026?

  1. Bushels
  2. Metric tonnes
  3. Imperial tons
  4. Kilograms
  5. Pounds
  6. Hundredweights

Tame hay and forage seed

30. Did you grow any alfalfa, other tame hay or forage seed in 2026?

Include hay grown on land rented from other operations and Crown or public land.

  1. Yes - Go to question 31
  2. No - Go to question 36

31. For the following crops, what was your total area and harvested area in 2026?

Exclude under-seeded areas.

Note: The harvested area remains the same despite multiple cuts (e.g., 3 cuts of 50 acres should be reported as 50 acres of harvested area).

  1. Alfalfa and alfalfa mixtures
  2. Other tame hay
  3. Forage seed

32. For the following types of hay, what is the number of bales you produced and the average weight?

Alfalfa cut as dry hay

  1. Round bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms
  2. Square or rectangular bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms

Alfalfa cut for silage

  1. Round bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms
  2. Square or rectangular bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms

Other tame hay cut as dry hay

  1. Round bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms
  2. Square or rectangular bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms

Other tame hay cut for silage

  1. Round bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms
  2. Square or rectangular bales
    • Number of bales
    • Average weight
    • Unit of measure
      1. Pounds
      2. Kilograms

Alfalfa and other tame hay harvested for silage

33. Do you store alfalfa or other tame hay cut for silage in silos?

  1. Yes - Go to question 34
  2. No - Go to question 35

34. What are the silos dimensions and percentage filled content of the silos?

1 metre = 3 feet approximately

Vertical silos: Diameter (in feet) / Height (in feet) / % full

  1. Silo 1
  2. Silo 2
  3. Silo 3

Horizontal silos: Length (in feet) / Width (in feet) / Height (in feet) / % full

  1. Silo 1
  2. Silo 2
  3. Silo 3

Silos bags: Diameter (in feet) / Length (in feet)

  1. Silo 1
  2. Silo 2
  3. Silo 3

35. What is the percent moisture content of the alfalfa and other tame hay harvested for silage, if applicable?

Percentage from 30.0% to 75.0%

Other land areas

36. Please report your areas in 2026 for the following:

  1. Summerfallow
    Include chemfallow areas, winterkilled areas (i.e., fall crop areas ploughed under but not reseeded) etc.
  2. Land for pasture or grazing
    Exclude areas to be harvested as dry hay, silage or forage seed, community pastures, co-operative
    grazing associations or grazing reserves.
    Note: If a field is used the same year for harvesting tame hay and as pasture, count it only once as a tame hay field.
  3. Other land
    e.g., farm buildings and farmyard , vegetable gardens, roads, woodland, swamp

Area in crops

38. What area of this operation is used for the following crops?

Unit of measure:

  1. Acres
  2. Hectares
  3. Arpents

 

  1. Field crops
  2. Hay
  3. Summerfallow
  4. Potatoes
  5. Fruit, berries and nuts
  6. Vegetables
  7. Sod
  8. Nursery products

Greenhouse area

39. What is the total area under glass, plastic or other protection used for growing plants?

Total area:

  1. Square feet
  2. Square metres 

Livestock - excluding birds

40. How many of the following animals are on this operation?

Report all animals on this operation, regardless of ownership, including those that are boarded,custom-fed or fed under contract.
Include all animals kept by this operation, regardless of ownership, that are pastured on a community pasture, grazing co-op or public land.
Exclude animals owned but kept on a farm, ranch or feedlot operated by someone else.

  1. Cattle and calves
  2. Pigs
  3. Sheep and lambs
  4. Mink
  5. Fox

Birds

41. How many of the following birds are on this operation?

Report all poultry on this operation, regardless of ownership, including those grown under contract.
Include poultry for sale and poultry for personal use.
Exclude poultry owned but kept on an operation operated by someone else.

  1. Hens and chickens
  2. Turkeys

Maple taps

42. What was the total number of taps made on maple trees last spring?

  1. Total number of taps

Honey bees

43. How many live colonies of honey bees (used for honey production or pollination) are owned by this operation?

Include bees owned, regardless of location.

  1. Number of colonies

Mushrooms

44. What is the total growing area (standing footage) for mushrooms?

Include mushrooms grown using beds, trays, tunnels or logs.

Total area:

  1. Square feet
  2. Square metres

Changes or events

45. Please indicate below, any changes or events that may have affected the reported values for this business or organization compared to the last reporting period

Mark all that apply:

  • Price changes in goods or services sold
  • Price changes in labour or raw materials
  • Natural disaster
  • Sold business units
  • Expansion
  • Other change or event - please specify:
    OR
  • No change or event

Contact person

Statistics Canada may need to contact the person who completed this questionnaire for further information.

If the contact person is the same as on cover page, please check [] and Go to " Feedback "

Otherwise, who is the best person to contact about this questionnaire?

  • First name
  • Last name
  • Title
  • Email address (example: user@example.gov.ca)
  • Telephone number (including area code)
  • Extension number (if applicable)
  • Fax number (including area code)

Feedback

How long did it take to complete this questionnaire?

Include the time spent gathering the necessary information.

  • Hours:
  • Minutes:

We invite your comments about this questionnaire.

Phased integration of NEXUS Highway traveller data in the Leading Indicator of International Arrivals to Canada

As of August 2026, enhancements implemented by the Canada Border Services Agency (CBSA) at land ports of entry enable Statistics Canada to incorporate information on travellers processed through the NEXUS Highway system into the Leading Indicator of International Arrivals to Canada.

The integration of NEXUS Highway traveller data will be phased in at all ports that receive NEXUS travellers from August 2026 to January 2027. As additional ports are integrated, coverage of international arrivals at land ports of entry with NEXUS travellers will continue to improve.

Users are advised to exercise caution when comparing data from the August 2026 leading indicator reference month onward with data from previous years, as the phased integration may affect historical comparability.

Ports which now include NEXUS travellers for the Leading indicator of international arrivals to Canada:  

  • Lansdowne (NEXUS enhancement implemented August 17, 2026)

* All other land ports reported through FCLI do not have Nexus lanes, thus the implementation of the enhanced system does not affect coverage.

Confidence Intervals Part 3: Factors Affecting the Width of a Confidence Interval

Catalogue number: 892000062026004

Release date: October 7, 2026

This video explores the three key factors that influence the width of a confidence interval: confidence level, population variability, and sample size. Through practical examples, viewers will learn how these factors affect the precision of survey estimates and gain a deeper understanding of how confidence intervals help communicate statistical uncertainty.

Data journey step

Analyze – Model

Data competency

  • Data analysis
  • Evaluating decisions based on data
  • Evidence based decision-making

Audience

Beginner

Suggested prerequisites

Confidence Intervals Part 2: Comparing Two Groups

Length

5:26

Cost

Free

Watch the video

Confidence Intervals Part 3: Factors Affecting the Width of a Confidence Interval - Transcript

Welcome back to our series on Confidence Intervals. In parts one and two, we explored point estimates, margins of error, confidence levels, and how to compare groups using confidence intervals.

In this final part, we'll examine a key question: what determines the width of a confidence interval?

These three elements determine the width of a confidence interval: the confidence level, variability within the population, and sample size.

Understanding these factors help us interpret estimates more accurately and communicate uncertainty, with confidence.

Let's start with the confidence level, the confidence level tells us how often the interval constructed using a given method would capture the true value if the sampling process were repeated many times.

A 95% confidence level means that if we repeated the same study many times, about 95 out of 100 intervals would include the true value.

A 99% confidence level makes us more certain, but the interval becomes wider. If we wanted 100% confidence level, we would make the interval as wide as possible, for example from 0 to 1 for a proportion.

However, such an interval is not useful since we already know, without analyzing any data that the true proportion must fall between 0 and 1.

All else being equal, a higher confidence level leads to a wider interval. Why? Because to be more certain that the interval contains the true value, we must allow it to include a broader range of plausible values. When you see both in 95% and 99% confidence interval around the same estimate. Note that the 99% interval extends further in both directions. This is expected the higher the confidence level, the wider the interval.

The second factor is variability. Variability refers to how much intervals in a population differ from the characteristic being measured.

All else being equal, if everyone is very similar, a small sample can provide a good estimate, but if individuals vary widely, you need more data to get a reliable overall picture.

If the measured characteristic is highly variable, estimates from different samples will also vary more.

This increased variability leads to larger margins of error and wider confidence intervals.

Consider two math classes taking the same test. A Regular class and an Advanced class. In the regular class, student scores vary widely, ranging from about 55 to 85.

When plotted, the scores spread across a wide range, indicating high variability. In the advanced class, most students score within a narrow range roughly between 85 and 95.

The scores are closely clustered, indicating low variability in practice. The distribution of a characteristic within a population is often not entirely unknown.

For example, before collecting data, we may have strong indications that the characteristic is not evenly distributed along genders or age groups.

This allows us to design a survey to improve accuracy, as we will see with the third factor sample size.

The third factor is sample size. Larger samples reduce uncertainty. The more observations there are, the more precise the estimates become. The smaller margin of error and the narrower the confidence interval.

For example, suppose a class has 100 students. A sample of ten students could produce an average far from the true class average, but a sample of 50 students will generally produce a result much closer to the true value.

An extreme approach would be to sample all but one student. This sample of 99 students would produce an estimate very close to the true value, since both are calculated using nearly the exact same data.

This increased precision directly results in a narrower interval.

These three elements: confidence level, variability within the population, and sample size work together to define every confidence interval you encounter.

So remember, the higher the confidence level, the wider the interval, the greater the variability. The wider the interval, the smaller the sample size, the wider the interval. When interpreting survey results are comparing groups. Keep these factors in mind.

They explain why some confidence intervals are narrow while others are wide, and indicate how much certainty we can reasonably claim.

Throughout this series, we've seen how confidence intervals can help us express what we know and what we don't know about a population.

So now that you understand the estimate itself, the uncertainty around it, and the factors that influence that uncertainty, you are better equipped to interpret survey results rigorously and communicate your findings with greater confidence.

(The Canada Wordmark appears.)

Confidence Intervals Part 2: Comparing Two Groups

Catalogue number: 892000062026003

Release date: October 7, 2026

This video explains how confidence intervals can be used to compare groups and assess whether observed differences are statistically meaningful. Through an example of physical activity levels among men and women across different age groups, viewers will learn how to use confidence interval overlap as a simple visual tool for interpreting differences and avoiding unsupported conclusions.

Data journey step

Analyze – Model

Data competency

  • Data analysis
  • Evaluating decisions based on data
  • Evidence based decision-making

Audience

Beginner

Suggested prerequisites

Confidence Intervals Part 1: Uncertainty in Estimation

Length

4:29

Cost

Free

Watch the video

Confidence Intervals Part 2: Comparing Two Groups - Transcript

Welcome back to our series on confidence intervals.

In Part 1, we focused on a single estimate and its confidence interval.

In this session, we will compare two groups using their confidence intervals and learn a quick visual check that helps us avoid making over-confident claims.

The guiding question we will be working with today is: "are men and women equally likely to meet the recommended guideline of 150 minutes of physical activity per week?".

We will begin with estimates, and then bring in their confidence intervals to interpret differences meaningfully.

Suppose we have data for men and women in 4 different age groups: 18 to 34, 35 to 49, 50 to 64, and 65 to 80.

These estimates show 52% of men aged 35 to 49 meet the 150 minute weekly guideline, compared to 36% for women in the same age group.

At first glance, it is tempting to conclude that relatively more men in this age group are active.

But before we do, we have to consider uncertainty.

We will do this using confidence intervals.

In part 1 of this series, we explained how confidence intervals surround an estimate with a range of plausible values, reflecting sampling uncertainty.

Narrower intervals suggest more precision; wider intervals reflect more uncertainty.

Today we'll be using confidence intervals to test whether relatively more men are active compared to women by doing a visual overlap check.

The visual overlap check is a quick, convenient and conservative way to screen for differences when you only have the published intervals and no access to the analytical file.

It is implemented as follows.

If the intervals do not overlap, then one may conclude to a statistically significant difference.

However, if the intervals do overlap, even slightly, then this visual check is inconclusive.

A formal test on the difference should then be conducted to confirm if the difference is significant, but this requires access to the analytical file and to software adapted to survey data.

We won't be getting into how that would be carried out in this video.

Using what we now know about the visual overlap test, let's add the confidence intervals to our chart.

For men aged 35 to 49, our estimate of 52% has a interval ranging from 47% to 57%. For women in the same age group, the 36% estimate has a interval ranging from 32% to 40%.

Because these confidence intervals do not overlap, we are allowed to conclude from the data that the true proportion differs by gender in this age group.

Now, consider a different age group: men and women aged 50 to 64.

Here, 40% of men are estimated to meet the recommended 150 minutes of physical activity every week, compared to 35% of women.

When we look more closely, we see that the confidence intervals overlap.

The visual check is therefore inconclusive, and we should avoid categorical statements based on this check alone.

A formal statistical test on the difference, using the underlying data, may still allow to conclude to a statistically significant difference between men and women in this age group, but we cannot do that from the visualization alone.

When we add confidence intervals to every age group and visually check for overlaps, we can summarize as follows: Relatively more men aged 18-34 and 35-49 meet the weekly physical activity recommendation compared to women in the same age groups.

However, the visual check for men and women aged 50-64 and 65-80 is inconclusive.

We should avoid drawing conclusions based on the chart alone.

Any time we try to communicate key findings, it's important to keep our wording aligned with what the chart or table can actually tell us.

In today's example, we learned that when confidence intervals do not overlap, you may safely conclude a statistically significant difference between men and women for the age groups concerned.

But when the intervals do overlap, one can only report that the visual check is inconclusive; a formal test would be needed to assess the difference.

Phrasing it this way keeps the message clear and measured without overreaching.

In the third and final part of our series, we'll see what affects the width of a confidence interval.

(The Canada Wordmark appears.)

Confidence Intervals Part 1: Uncertainty in Estimation

Catalogue number: 892000062026002

Release date: October 7, 2026

Confidence intervals help us understand the uncertainty behind survey estimates. This video explains the three key components of a confidence interval: point estimates, margins of error, and confidence levels, and shows how to interpret them in real-world Statistics Canada data.

Data journey step

Analyze – Model

Data competency

  • Data analysis
  • Evaluating decisions based on data
  • Evidence based decision-making

Audience

Beginner

Suggested prerequisites

N/A

Length

6:10

Cost

Free

Watch the video

Confidence Intervals Part 1: Uncertainty in Estimation - Transcript

Suppose you read this in the news: 23% of Canadian households experienced food insecurity in the past year.

You may even read that "This estimate is based on a random sample of 2000 Canadians, plus or minus 2 percentage points, 19 times out of 20." Let's break down what this statement actually tells us, because it's not just filler. It's how we communicate both what we know, and what we don't know.

Let's start with the point estimate. What's a point estimate you ask? Well, this is the estimate we make about a population based on the data we've collected from the sample.

For example, let's say we want to know how many Canadian households experienced food insecurity in the past year.

We survey a random sample of 2,000 households, and we find that 23% reported experiencing food insecurity.

That 23% is the point estimate, and it's our starting point.

Here's something important to remember:

The true value is fixed, but unknown. This is what we want to know about the population, a quantity or a characteristic. There is a real percentage out there.

We just can't know exactly what it is unless we survey every household in the country, which impossible. Instead, we estimate it using a random sample.

Let's look at it another way.

In this image, the blue dots represent the entire population of Canada. Because we can't survey every household in the country, we survey a random sample of 2,000 households, represented by the yellow stars.

With this sample, we obtain a point estimate of 23% of Canadian households having experienced food insecurity in the last year.

By taking another random sample, we could obtain a different estimate.

This time, the sample is shown in red and estimates that 21% of households in Canada experienced food insecurity in the past year.

This leads us to our Main Idea 2: the margin of error.

Because we used a sample instead of surveying every household in Canada, how much might that 23% estimate vary if we asked a totally different group or sample?

That's where the margin of error comes in. It tells us how much our point estimate might vary.

It's normal to have uncertainty when you use samples. The magnitude of the margin of error reflects how uncertain we are about the point estimate.

To achieve smaller margins of error—or more precision— a larger sample is usually needed.

In our example, the sample of 2,000 households resulted in a margin of error of plus or minus 2 percentage points around our estimated value of 23%.

But what if we wanted to achieve higher precision?

A way to do this is to take a larger random sample. Larger samples reduce the uncertainty associated with point estimates.

In this example using a larger sample size, the width of the interval around the estimated value is narrower.

Finally, let's talk about the confidence level. You'll often hear the phrase "19 times out of 20", or "95% confidence", associated with an estimate. But what does that really mean?

19 times out of 20 means we are 95% confident that the true value we're trying to estimate is inside our confidence interval.

So if we used different samples over and over, 95% of those confidence intervals would contain the true value but 5% wouldn't.

Remember that the true value is fixed. We are talking about the error rate of our method - it captures the true value 95% of the time but fails to do so 5% of the time.

Before we wrap up, let's take quick look at how you can spot confidence intervals in the real world.

This chart can be found on Statistics Canada's website, and if you look closely, you'll see little vertical and horizontal lines on each bar creating a buffer area around the estimates. That's the confidence interval. And it's showing you how much uncertainty is built into the estimate. For example, the first bar represents a point estimate of 30% for the year 2018, while its margin of error is plus or minus three percentage points.

This table here, also shows confidence intervals, this time as lower and upper bounds next to the estimate.

So now, when you are looking at StatCan data, or any survey reporting confidence intervals, you'll know what those ranges mean and why they matter.

So here are the three things to remember about confidence intervals:

  • First, the Point Estimate is the value we get from the collected data. In our case, 23%.
  • Second, the Margin of Error is the range around that value, reflecting the uncertainty due to sampling. In this video, it's plus or minus 2 percentage points, which gives us a range of 21% to 25%.
  • Finally, the Confidence Level is how often this method gives us an interval that covers the true population value. Remember, at 95%, we're saying this approach works MOST of the time, but not ALL the time.

Remember…the truth is out there. The true value, what we want to know about the population of interest, is fixed, but unknown. And confidence intervals are how we responsibly estimate that value and express how sure we are.

Watch our follow-up videos to learn more about:

  • the elements that impact the width of a confidence interval, and
  • how confidence intervals can be used to determine whether two estimates are significantly different.

(The Canada Wordmark appears.)

Labour Market Indicators – October 2026

In October 2026, questions measuring the Labour Market Indicators were added to the Labour Force Survey as a supplement.
Questionnaire flow within the collection application is controlled dynamically based on responses provided throughout the survey. Therefore, some respondents will not receive all questions, and there is a small chance that some households will not receive any questions at all. This is based on their answers to certain LFS questions.

Labour Market Indicators

ENTRY_Q01 / EQ 1 - From the following list, please select the household member that will be completing this questionnaire on behalf of the entire household.

SAT_Q01 / EQ 2 – Using a scale of 0 to 10, where 0 means “Very dissatisfied” and 10 means “Very satisfied,” in general, how satisfied are you with your main job or business? 

  1. Very dissatisfied 
  2.  
  3.  
  4.  
  5.  
  6.  
  7.  
  8.  
  9.  
  10.  
  11. Very satisfied 

CHS_I01 – The following question is about the financial situation of your household. 

CHS_Q01 / EQ3 – Over the last month, that is since September 15 to today, how difficult or easy was it for your household to meet its financial needs in terms of transportation, housing, food, clothing and other necessary expenses? 

Would you say:

  1. Very difficult
  2. Difficult
  3. Neither difficult nor easy
  4. Easy
  5. Very easy

Concordance: Harmonized Commodity Description and Coding System (HS) 2012 - Harmonized Commodity Description and Coding System (HS) 2017 at the 6-digit level - HS6 (Exports- Imports)

As part of the 2017 World Customs Organization (WCO) amendments, a number of codes have been terminated and recoded.

Updates at the 6-digit level are made every 5 years by the WCO, in order to reflect international standards and trade patterns.

This concordance table lists the terminated HS codes alongside with the new 2017 recoded HS codes at the 6-digit level.

These changes will take effect January 1st, 2017.

Concordance: Harmonized Commodity Description and Coding System (HS) 2012 - Harmonized Commodity Description and Coding System (HS) 2017 at the 6-digit level - SH6 (Export- Import)
2012 Terminated HS Codes2017 HS Codes
0301.930301.93
0301.990301.93
0301.990301.99
0302.110302.11
0302.110302.99
0302.130302.13
0302.130302.99
0302.140302.14
0302.140302.99
0302.190302.19
0302.190302.99
0302.210302.21
0302.210302.99
0302.220302.22
0302.220302.99
0302.230302.23
0302.230302.99
0302.240302.24
0302.240302.99
0302.290302.29
0302.290302.99
0302.310302.31
0302.310302.99
0302.320302.32
0302.320302.99
0302.330302.33
0302.330302.99
0302.340302.34
0302.340302.99
0302.350302.35
0302.350302.99
0302.360302.36
0302.360302.99
0302.390302.39
0302.390302.99
0302.410302.41
0302.410302.99
0302.420302.42
0302.420302.99
0302.430302.43
0302.430302.99
0302.440302.44
0302.440302.99
0302.450302.45
0302.450302.99
0302.460302.46
0302.460302.99
0302.470302.47
0302.470302.99
0302.510302.51
0302.510302.99
0302.520302.52
0302.520302.99
0302.530302.53
0302.530302.99
0302.540302.54
0302.540302.99
0302.550302.55
0302.550302.99
0302.560302.56
0302.560302.99
0302.590302.59
0302.590302.99
0302.710302.71
0302.710302.99
0302.720302.72
0302.720302.99
0302.730302.73
0302.730302.99
0302.740302.74
0302.740302.99
0302.790302.79
0302.790302.99
0302.810302.81
0302.810302.92
0302.810302.99
0302.820302.82
0302.820302.99
0302.830302.83
0302.830302.99
0302.840302.84
0302.840302.99
0302.850302.85
0302.850302.99
0302.890302.49
0302.890302.73
0302.890302.89
0302.890302.99
0302.900302.91
0303.110303.11
0303.110303.99
0303.120303.12
0303.120303.99
0303.130303.13
0303.130303.99
0303.140303.14
0303.140303.99
0303.190303.19
0303.190303.99
0303.230303.23
0303.230303.99
0303.240303.24
0303.240303.99
0303.250303.25
0303.250303.99
0303.260303.26
0303.260303.99
0303.290303.29
0303.290303.99
0303.310303.31
0303.310303.99
0303.320303.32
0303.320303.99
0303.330303.33
0303.330303.99
0303.340303.34
0303.340303.99
0303.390303.39
0303.390303.99
0303.410303.41
0303.410303.99
0303.420303.42
0303.420303.99
0303.430303.43
0303.430303.99
0303.440303.44
0303.440303.99
0303.450303.45
0303.450303.99
0303.460303.46
0303.460303.99
0303.490303.49
0303.490303.99
0303.510303.51
0303.510303.99
0303.530303.53
0303.530303.99
0303.540303.54
0303.540303.99
0303.550303.55
0303.550303.99
0303.560303.56
0303.560303.99
0303.570303.57
0303.570303.99
0303.630303.63
0303.630303.99
0303.640303.64
0303.640303.99
0303.650303.65
0303.650303.99
0303.660303.66
0303.660303.99
0303.670303.67
0303.670303.99
0303.680303.68
0303.680303.99
0303.690303.69
0303.690303.99
0303.810303.81
0303.810303.92
0303.810303.99
0303.820303.82
0303.820303.99
0303.830303.83
0303.830303.99
0303.840303.84
0303.840303.99
0303.890303.25
0303.890303.59
0303.890303.89
0303.890303.99
0303.900303.91
0304.390304.39
0304.490304.39
0304.490304.47
0304.490304.48
0304.490304.49
0304.510304.51
0304.590304.51
0304.590304.56
0304.590304.57
0304.590304.59
0304.690304.69
0304.890304.69
0304.890304.88
0304.890304.89
0304.930304.93
0304.990304.93
0304.990304.96
0304.990304.97
0304.990304.99
0305.310305.31
0305.390305.31
0305.390305.39
0305.440305.44
0305.490305.44
0305.490305.49
0305.590305.52
0305.590305.53
0305.590305.54
0305.590305.59
0305.640305.64
0305.690305.64
0305.690305.69
0306.210306.31
0306.210306.91
0306.220306.32
0306.220306.92
0306.240306.33
0306.240306.93
0306.250306.34
0306.250306.94
0306.260306.35
0306.260306.95
0306.270306.36
0306.270306.95
0306.290306.39
0306.290306.99
0307.190307.12
0307.190307.19
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