France is the fixed origin in this UNESCO Institute for Statistics measure; the 77 rows are destinations where internationally mobile students from France were observed in 2020. That distinction matters because the figures do not describe foreign students entering France. They compare the female and male values for France-origin student mobility across destination countries and territories.
The adjusted gender parity index (GPIA) spans a very wide range in this slice of the data. The lowest observation is 0.0969, the highest is 2.0, and the median is 1.04663. Only 9 of the 77 destinations fall inside the commonly used 0.97–1.03 parity interval. Another 29 are below 0.97 and 39 are above 1.03, so a median near 1 should not be mistaken for near-parity everywhere.
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The 77 destinations form a broad rather than tightly balanced distribution
There are 40 observations above 1, 30 below 1 and 7 exactly equal to 1. The middle half of the dataset runs from roughly 0.857 to 1.309. That interquartile span is wide enough to show that the destination pattern is not concentrated narrowly around parity, even though the mean (1.069) and median (1.047) sit relatively close to the reference value of 1.
Seven destinations have an exact value of 1.000: Cuba, the Dominican Republic, Ecuador, Oman, Qatar, El Salvador and Ukraine. Greece at 0.97872 and Switzerland at 1.02204 bring the count inside the 0.97–1.03 band to nine. Canada, at 0.96629, sits just below that interval, while Türkiye at 1.04663 is just above it and also happens to match the dataset median.
Near-parity values are useful anchors for reading the rest of the series
A GPIA of 1 means that the female and male values of the underlying indicator are equal. Moving away from 1 indicates a larger disparity. Greece and Switzerland are especially useful examples because they lie on opposite sides of 1 at nearly the same distance. The adjusted form of the index is designed to make that distance more comparable than the ordinary female-to-male ratio.
Other destinations show a gradual move away from parity rather than an abrupt break. Chile is 0.93333, Latvia 0.92857 and Estonia 0.92308 on the lower side. On the upper side, Czechia is 1.08696, Denmark 1.09779 and Norway 1.11486. These values say something about relative gender composition for this specific indicator; they do not say how many students were involved.
The upper side includes several very large adjusted disparities
Four destinations—Benin, Georgia, the Republic of Moldova and Mauritania—have values of 2.000. Kazakhstan is 1.750, Serbia 1.66667, Côte d’Ivoire 1.600 and Macao SAR 1.55556. Andorra and Belarus are both 1.500, followed by Malta at 1.47826 and Belgium at 1.44223. These observations sit far from the parity point and therefore represent large differences between the female and male indicator values.
The adjusted index is essential to interpreting those numbers correctly. UIS starts with a female-to-male ratio. When the ratio is at or below 1, the adjusted value is the same as that ratio. When the ratio exceeds 1, UIS transforms it by subtracting the inverse ratio from 2. This produces a scale from 0 to 2 that is symmetric around 1. As a result, a GPIA of 1.5 is not simply a statement that there are 1.5 women for every man, and a boundary value of 2.0 should not be translated into a simple two-to-one count claim without the underlying sex-specific data.
The lower tail is equally important
The smallest values occur in Saudi Arabia (0.0969), Egypt (0.125), Iran (0.200), Jordan (0.26923), Bahrain (0.30769) and Bosnia and Herzegovina (0.33333). Cyprus records 0.44444, while the Democratic Republic of the Congo, Panama and Viet Nam each record 0.500. For this student-count indicator, values below 1 mean that the female indicator value is lower than the male value; the farther the number lies below 1, the larger the relative difference.
Those extreme figures should not be confused with the size of a student flow. A parity index is a relative measure. A destination can have a striking value even when the underlying number of students is small, and this dataset does not provide the female and male counts needed to judge the scale behind each ratio. For the same reason, the chart is best read as a composition comparison, not as a ranking of important destinations for French students.
Selected values show how the scale behaves
| Destination | GPIA | Interpretation |
|---|---|---|
| Saudi Arabia | 0.0969 | Far below the parity point |
| Egypt | 0.1250 | Far below the parity point |
| Bosnia and Herzegovina | 0.3333 | Large lower-side disparity |
| Greece | 0.9787 | Within the 0.97–1.03 parity band |
| Cuba | 1.0000 | Equal female and male indicator values |
| Switzerland | 1.0220 | Within the 0.97–1.03 parity band |
| Türkiye | 1.0466 | Observation equal to the dataset median |
| Belgium | 1.4422 | Large upper-side disparity |
| Kazakhstan | 1.7500 | Very large upper-side disparity |
| Benin | 2.0000 | Upper boundary of the adjusted scale |
These examples are intentionally spread across the scale. They are not a list of “best” or “worst” destinations. The purpose is to show the difference between near-parity observations, moderate departures and values at the edges of the adjusted scale. Small numerical gaps should also be treated cautiously because the public series is rounded and the underlying student counts are not included here.
What the index can answer—and what it cannot
GPIA is well suited to one narrow question: how similar were the female and male values of this France-origin mobility indicator in each destination? It provides a common reference point across 77 places and lets a reader identify destinations that are near parity or far from it without mixing different formulas from country to country.
It does not measure the quality of higher education, the attractiveness of a destination, tuition costs, visa rules, scholarship access, subject choices or post-study employment. It also cannot explain why a gender difference exists. Answering those questions would require additional evidence such as student counts by sex, fields of study, education level, multi-year trends and destination-specific institutional information.
The year also matters. These are 2020 observations, not a permanent profile of French student mobility. International mobility can change quickly, and ratios can move sharply where the number of students is limited. The safest interpretation is therefore descriptive: this is how the female-male balance of the specified indicator looked across the available destinations in 2020.
Data source and interpretation method
The country values come from the UNESCO UIS API series E.5T8.FOREIGN.ORG250.GPIA. UIS explains the adjusted parity method in its official parity-index definition: a value of 1 marks equality between the two group values, and the adjusted transformation makes departures above and below 1 comparable on a 0–2 scale. The comparison here uses the 77 reported observations and does not replace missing values with zero.
A sorted distribution chart is more informative for this particular slice than a choropleth map. The main question is distance from the parity point, not geographic adjacency. Plotting every destination on the same vertical scale makes the narrow parity band, the long lower tail and the upper boundary values visible without suggesting that neighboring countries share a cause that the data do not establish.
Frequently Asked Questions
What does a GPIA of 1.000 mean?
It means the female and male values of the underlying indicator are equal. UIS commonly treats 0.97–1.03 as a range consistent with parity.
How many destinations were within the parity band in 2020?
9 of the 77 destinations were between 0.97 and 1.03. Seven were exactly 1.000, with Greece and Switzerland also inside the band.
Does a GPIA of 1.5 or 2.0 mean 1.5 or 2 women per man?
No. Values above 1 are transformed by the adjusted-parity formula, so the published GPIA is not a direct female-to-male multiplier.
Can this index show which destinations were most popular with students from France?
No. GPIA describes relative gender balance, not the number of students, destination popularity, education quality, cost or visa conditions.
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