Canada vs Syrian Arab Republic: ILO: ILO Modelled Estimates Employment in agriculture ILO … Female

Canada
69.05 1000 No
in 2025
Syrian Arab Republic
68.47 1000 No
in 2025
Canada rank
116th
Syrian Arab Republic rank
117th

ILO: ILO Modelled Estimates Employment in agriculture ILO … Female over time

  • Canada
  • Syrian Arab Republic
0100200300400500199120082025

How they compare

Canada currently reports 69.05 1000 No against 68.47 1000 No in Syrian Arab Republic, a difference of 0.58 1000 No.

The two have swapped places 1 time across 35 shared years of data; in 1991 it was Syrian Arab Republic ahead.

Canada ranks 116th and Syrian Arab Republic ranks 117th of 194 countries.

Across the 4 decades both report, Canada averaged higher in 2 and Syrian Arab Republic in 2.

Head to head by decade

Decade Canada Syrian Arab Republic Difference Ahead
1990s 134.96 1000 No 347.95 1000 No 212.98 1000 No Syrian Arab Republic
2000s 101.89 1000 No 306.74 1000 No 204.85 1000 No Syrian Arab Republic
2010s 92.22 1000 No 67.96 1000 No 24.26 1000 No Canada
2020s 79.41 1000 No 66.85 1000 No 12.56 1000 No Canada

Averages of every year both report within each decade.

Frequently asked questions

Which has higher ilo - ilo modelled estimates — employment in agriculture - ilo, Canada or Syrian Arab Republic?
Canada, at 69.05 1000 No against 68.47 1000 No in Syrian Arab Republic as of 2025.
What is the difference in ilo - ilo modelled estimates — employment in agriculture - ilo between Canada and Syrian Arab Republic?
0.58 1000 No, with Canada ahead.
How many years of comparable data are there for Canada and Syrian Arab Republic?
35 years are reported by both, from 1991 to 2025.
How do Canada and Syrian Arab Republic rank globally for ilo - ilo modelled estimates — employment in agriculture - ilo?
Canada ranks 116th and Syrian Arab Republic ranks 117th of 194 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as ILO - ILO Modelled Estimates — Employment in agriculture - ILO modelled estimates — Female — Value. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

Canada vs Syrian Arab Republic: ILO - ILO Modelled Estimates — Employment in agriculture - ILO. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 24 October 2026, from https://agriculture.statizoid.com/compare/ilo-ilo-modelled-estimates-employment-in-agriculture-ilo-modelled-estimates-female-value/canada/syrian-arab-republic-2/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY-NC-SA 3.0 IGO (FAO); please keep the attribution.

<a href="https://agriculture.statizoid.com/compare/ilo-ilo-modelled-estimates-employment-in-agriculture-ilo-modelled-estimates-female-value/canada/syrian-arab-republic-2/">Canada vs Syrian Arab Republic: ILO - ILO Modelled Estimates — Employment in agriculture - ILO</a> — Statizoid

About this data

Indicator
ILO - ILO Modelled Estimates — Employment in agriculture - ILO modelled estimates — Female — Value
Unit
1000 No
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
227 places, 7,928 data points, 1991–2025
Last refreshed

The FAOSTAT Employment indicators domain focuses on indicators related to employment in agrifood systems and rural areas. The update is performed yearly, using data from the International Labour Organization (ILO) database that contains a rich set of indicators from a wide range of topics related to labour statistics. The indicators published in FAOSTAT are derived from the labour force statistics (LFS) and rural and urban labour markets (RURURB) databases of the ILOSTAT database. In addition, the ILO modelled estimates and projections (ILOEST) are used to provide information on employment in agriculture. FAOSTAT also publishes indicators on employment in agrifood systems (AFS) from 2000 at the national, regional, and global levels, using a methodology developed by the FAO to estimate the number of people employed within these systems.