Trend · rank 192 of 250

Gender participation divergence

Women's access to employment and advancement is improving unevenly and reversing in some places, creating national differences in usable talent, household resilience and returns on education.

Human CapitalPeople, health & workwork skillsinequality

Second pass: Carried forward from the first pass, where it was Gender equality & inclusion. Held by all three panel models.

Sensitivity and network position

Rank
192of 250
Sensitivity
5.8rank 195
Breadth
0of 20 scenarios High or above
PageRank
31.0rank 144
Eigenvector
2.5
Betweenness
0.0
Links
10trends at Moderate similarity or above
Composite
14.0

Attention over three years

How much this trend is read about on Wikipedia and searched for on Google, week by week, set against the typical trend in the list so that what moves every trend at once is taken out. 100 is this trend's own three-year average. The score measures public attention, which is not the same as the strength of the force: a trend can deepen unnoticed, and a news event can lift attention for a fortnight.

Share of attention
0.11%rank 180 of 250 · a year earlier 0.12%
Now
77
Over a year
−11%Steady
Over three years
−23%
Peak
2093 Mar 2024
Sources
Bothagreement 0.78
Coverage
12languages · 53 nations

Trailing 4-week average. 100 is this trend’s three-year average.

By language

Wikipedia reading in each language edition where the trend’s pages are read enough to measure (12 of 28). Share is of all the readers counted.

LanguageShareNowOver a yearThree years
English51%87−1%
Spanish13%53−7%
German8%76−17%
French8%70−9%
Japanese6%114+9%
Russian5%114+14%
Italian3%82−2%
Ukrainian2%95+22%
Persian1%120+37%
Polish1%76+15%
Korean1%127+42%
Arabic1%146+49%

By country

Google search interest over the three years, as a share of each country’s searching. 100 is the nation where interest is highest. The search terms are English, which favours countries that search in English.

The 12 highest of 53 nations with a reading. All countries (CSV).

By region and G20 member

Attention to this trend inside each place, from Google searches made in its countries and Wikipedia reading in the languages mostly read there, averaged where both exist. Each line compares the trend with its own past in that place; the lines do not compare places.

Regions

PlaceRead fromNow90 days1 year3 yearsThree years
North AmericaGoogle in 2 countries + Wikipedia in English74−17%−6%−37%
EuropeGoogle in 6 countries + Wikipedia in German, French, Italian, Polish67−20%−17%−47%
Indo-PacificGoogle in 5 countries + Wikipedia in Japanese, Korean101+10%+16%−1%
South AsiaGoogle in 1 country82+17%+2%−24%
Gulf and Middle EastGoogle in 1 country + Wikipedia in Persian, Arabic123+33%+9%+41%
Latin America and CaribbeanGoogle in 2 countries + Wikipedia in Spanish61−13%−16%−52%
Russia and EurasiaWikipedia in Russian, Ukrainian108+4%+16%+18%

G20 members

PlaceRead fromNow90 days1 year3 yearsThree years
AustraliaGoogle46−2%−33%−37%
BrazilGoogle81+10%−19%−43%
CanadaGoogle66−13%+16%−48%
FranceGoogle + Wikipedia in French79+9%−12%−36%
GermanyGoogle + Wikipedia in German68−17%−21%−41%
IndiaGoogle82+17%+2%−24%
IndonesiaGoogle990%+47%+25%
ItalyGoogle + Wikipedia in Italian56−50%−23%−58%
JapanGoogle + Wikipedia in Japanese101+35%0%−9%
South KoreaGoogle + Wikipedia in Korean129−10%+85%+35%
MexicoGoogle54−16%−28%−60%
RussiaWikipedia in Russian114+3%+14%+45%
TürkiyeGoogle115+41%−14%+47%
United KingdomGoogle38−36%−51%−70%
United StatesGoogle + Wikipedia in English74−18%−10%−38%

Share of attention by region

GINC Share of Attention: this trend's share of all the public attention the trends in the list draw, worldwide and in each region, week by week (a 4-week average). Each place is read from the Wikipedia languages mostly read there and Google searching in its countries; where a place's language is shared with others, as English is, Google stands alone.

PlaceShare, last 13 weeksRank thereA year earlierRead from
World0.11%180 of 2500.12%Wikipedia reading in all 28 languages, and Google searching worldwide
Asia Pacific0.10%193 of 2500.10%Wikipedia reading in the region's own languages, not English; Google searching in 15 countries, not China
Europe0.13%162 of 2500.18%German, French, Italian, Polish, Dutch and Swedish reading; Google searching in 10 countries, the UK among them
Africa0.02%223 of 2500.02%Google searching in 7 countries; Afrikaans and Swahili reading reaches too few trends to count
South America0.13%166 of 2500.18%Spanish and Portuguese reading, Spanish also read in Spain; Google searching in 5 countries
North America0.07%160 of 2490.10%Google searching in the United States, Canada and Mexico; English reading cannot be split by country
Oceania0.11%131 of 2490.13%Google searching in Australia and New Zealand; English reading cannot be split by country
United States0.05%180 of 2490.06%Google searching; English reading cannot be split by country
United Kingdom0.06%150 of 2490.08%Google searching; English reading cannot be split by country
India0.02%191 of 2490.02%Google searching; Hindi, Bengali and Tamil reading reaches too few trends to count, and English cannot be split by country
China···Wikipedia and Google are blocked in China; no open source counts reading there
Russia0.17%141 of 2030.16%Russian reading, which is also done across the former Soviet states; Google's figures for Russia cannot be bought
Japan0.32%101 of 2500.33%Japanese reading and Google searching
Germany0.24%102 of 2500.31%German reading and Google searching
France0.13%140 of 2500.20%French reading, also done in Africa and Canada, and Google searching
Italy0.14%135 of 2500.27%Italian reading and Google searching
South Korea0.14%137 of 2500.10%Korean reading and Google searching
Indonesia0.01%212 of 2500.02%Google searching; Indonesian reading reaches too few trends to count
Brazil0.09%163 of 2500.10%Portuguese reading and Google searching
Türkiye0.01%68 of 2500.01%Google searching; Turkish reading reaches too few trends to count

Relation to each scenario

A trend relates to a scenario when it changes how likely the scenario is, how hard it lands, or is itself sharply changed by it. Each score is the median of three scores given separately by the members of the model panel.

RelationScenarioFamily
3 · ModerateA validated farming package raises water-efficient output S16 ↗Energy, climate and resources
2 · LowAn AI deployment step causes abrupt labour displacement S08Technology and infrastructure
2 · LowA public service platform reaches inclusive operation S18 ↗Technology and infrastructure
0 · Not relatedCritical trade divides into rival blocs S01Economic and trade
0 · Not relatedA global funding seizure reaches sovereign balance sheets S02Economic and trade
0 · Not relatedA regional war closes a globally important sea route S03Geopolitical and security
0 · Not relatedHybrid coercion ends in an infrastructure blackout S04Geopolitical and security
0 · Not relatedA disputed transfer of power breaks effective government S05Geopolitical and security
0 · Not relatedTwo breadbasket failures trigger a food availability crisis S06Energy, climate and resources
0 · Not relatedA major disaster disables the national economic core S07Energy, climate and resources
0 · Not relatedA cryptographic breakthrough invalidates digital trust S09Technology and infrastructure
0 · Not relatedA novel respiratory pathogen exceeds health surge capacity S10Health
0 · Not relatedA creditor agreement releases fiscal capacity S11 ↗Economic and trade
0 · Not relatedA cross-regional market access compact redirects investment S12 ↗Economic and trade
0 · Not relatedA great-power agreement lowers economic security barriers S13 ↗Geopolitical and security
0 · Not relatedA verified Middle East settlement restores access S14 ↗Geopolitical and security
0 · Not relatedCheap firm clean power becomes available at scale S15 ↗Energy, climate and resources
0 · Not relatedAI-directed research produces a reproducible discovery step S17 ↗Technology and infrastructure
0 · Not relatedAffordable preventive treatments reduce chronic illness S19 ↗Health
0 · Not relatedA live outbreak proves rapid distributed pandemic defence S20 ↗Health

Similarity = 0.3 × shared tags (Jaccard) + 0.3 × likeness of scenario profiles (cosine) + 0.3 × likeness of names and descriptions (TF-IDF cosine) + 0.1 if in the same capability domain, cut into seven levels at 0.12, 0.22, 0.33, 0.45, 0.58, 0.72. Shown at Moderate and above.

SimilarityTrendThemeRank
5 · Very highEntrenched opportunity inequalityPeople, health & work9
5 · Very highFoundational learning deficitsPeople, health & work162
4 · HighYouth population expansionPeople, health & work146
4 · HighGraduate skill mismatchPeople, health & work178
3 · ModerateTechnical & occupational skill shortagesPeople, health & work19
3 · ModerateTechnology diffusion & productivity gapsPeople, health & work24
3 · ModerateAI & knowledge-work automationPeople, health & work53
3 · ModerateInformal employment persistencePeople, health & work84
3 · ModerateLifelong learning & digital reskillingPeople, health & work132
3 · ModerateYouth employment exclusionPeople, health & work177