Trend · rank 2 of 250

Civil service capability & pay

Public pay, career structures and morale are losing ground to private competition for technical and specialist staff, limiting the state's ability to recruit and retain the people needed to design and implement policy.

Governance & IntegrityState capacity & governanceinstitutionswork skills

Second pass: Carried forward from the first pass unchanged. Held by two of the three panel models.

Sensitivity and network position

Rank
2of 250
Sensitivity
28.3rank 4
Breadth
1of 20 scenarios High or above
PageRank
85.7rank 6
Eigenvector
74.6
Betweenness
96.8
Links
27trends at Moderate similarity or above
Composite
74.1

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
0.05%rank 222 of 250 · a year earlier 0.05%
Now
68
Over a year
−4%Steady
Over three years
−43%
Peak
36617 Dec 2023
Sources
Bothagreement 0.37
Coverage
13languages · 10 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 (13 of 28). Share is of all the readers counted.

LanguageShareNowOver a yearThree years
English84%69−15%
German4%58−34%
French3%83−10%
Russian2%102+45%
Polish2%81−12%
Hindi1%48+30%
Spanish1%72−22%
Thai1%113+31%
Arabic1%102−11%
Ukrainian0%71−13%
Italian0%95−1%
Vietnamese0%109+114%
Swedish0%88−5%

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.

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 1 country + Wikipedia in English68+31%−5%−67%
EuropeGoogle in 6 countries + Wikipedia in German, French, Italian, Polish, Swedish76+5%−23%−35%
Indo-PacificGoogle in 4 countries + Wikipedia in Vietnamese, Thai102+1%+1%+6%
South AsiaGoogle in 1 country + Wikipedia in Hindi90+1%+39%−29%
Gulf and Middle EastWikipedia in Arabic102−2%−11%+46%
Latin America and CaribbeanGoogle in 3 countries + Wikipedia in Spanish73−6%−30%−34%
Russia and EurasiaGoogle in 1 country + Wikipedia in Russian, Ukrainian100+12%+4%−7%

G20 members

PlaceRead fromNow90 days1 year3 yearsThree years
FranceGoogle + Wikipedia in French90+32%−13%−17%
GermanyGoogle + Wikipedia in German58−12%−38%−59%
IndiaGoogle + Wikipedia in Hindi90+1%+39%−29%
IndonesiaGoogle102+33%−12%−8%
ItalyGoogle + Wikipedia in Italian93+8%−13%−16%
South KoreaGoogle88+121%−43%−15%
MexicoGoogle68+25%−40%−43%
RussiaWikipedia in Russian102−1%+45%+2%
United KingdomGoogle45−23%−51%−50%
United StatesGoogle + Wikipedia in English68+31%−5%−67%

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
World0.05%222 of 2500.05%Wikipedia reading in all 28 languages, and Google searching worldwide
Asia Pacific0.13%172 of 2500.08%Wikipedia reading in the region's own languages, not English; Google searching in 15 countries, not China
Europe0.34%75 of 2500.40%German, French, Italian, Polish, Dutch and Swedish reading; Google searching in 10 countries, the UK among them
Africa0.03%201 of 2500.05%Google searching in 7 countries; Afrikaans and Swahili reading reaches too few trends to count
South America0.11%181 of 2500.13%Spanish and Portuguese reading, Spanish also read in Spain; Google searching in 5 countries
North America0.04%193 of 2490.05%Google searching in the United States, Canada and Mexico; English reading cannot be split by country
Oceania0.01%242 of 2490.01%Google searching in Australia and New Zealand; English reading cannot be split by country
United States0.05%188 of 2490.03%Google searching; English reading cannot be split by country
United Kingdom0.03%199 of 2490.03%Google searching; English reading cannot be split by country
India0.00%245 of 2490.00%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
Russia0.08%183 of 2030.06%Russian reading, which is also done across the former Soviet states; Google's figures for Russia cannot be bought
Japan0.01%248 of 2500.01%Japanese reading and Google searching
Germany0.64%43 of 2500.81%German reading and Google searching
France0.27%89 of 2500.37%French reading, also done in Africa and Canada, and Google searching
Italy0.06%194 of 2500.08%Italian reading and Google searching
South Korea0.06%188 of 2500.06%Korean reading and Google searching
Indonesia0.15%100 of 2500.06%Google searching; Indonesian reading reaches too few trends to count
Brazil0.00%250 of 2500.00%Portuguese reading and Google searching
Türkiye0.00%247 of 2500.00%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
4 · HighA public service platform reaches inclusive operation S18 ↗Technology and infrastructure
3 · ModerateA disputed transfer of power breaks effective government S05Geopolitical and security
2 · LowA global funding seizure reaches sovereign balance sheets S02Economic and trade
2 · LowHybrid coercion ends in an infrastructure blackout S04Geopolitical and security
2 · LowA major disaster disables the national economic core S07Energy, climate and resources
2 · LowAn AI deployment step causes abrupt labour displacement S08Technology and infrastructure
2 · LowA cryptographic breakthrough invalidates digital trust S09Technology and infrastructure
2 · LowA novel respiratory pathogen exceeds health surge capacity S10Health
2 · LowA creditor agreement releases fiscal capacity S11 ↗Economic and trade
2 · LowAffordable preventive treatments reduce chronic illness S19 ↗Health
2 · LowA live outbreak proves rapid distributed pandemic defence S20 ↗Health
1 · Very lowCritical trade divides into rival blocs S01Economic and trade
1 · Very lowA regional war closes a globally important sea route S03Geopolitical and security
1 · Very lowTwo breadbasket failures trigger a food availability crisis S06Energy, climate and resources
1 · Very lowA cross-regional market access compact redirects investment S12 ↗Economic and trade
1 · Very lowA great-power agreement lowers economic security barriers S13 ↗Geopolitical and security
1 · Very lowA verified Middle East settlement restores access S14 ↗Geopolitical and security
1 · Very lowCheap firm clean power becomes available at scale S15 ↗Energy, climate and resources
1 · Very lowA validated farming package raises water-efficient output S16 ↗Energy, climate and resources
1 · Very lowAI-directed research produces a reproducible discovery step S17 ↗Technology and infrastructure

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
4 · HighState capacity & deliveryState capacity & governance1
4 · HighRule of law & judicial independenceState capacity & governance3
4 · HighExecutive overreach & emergency powersState capacity & governance4
4 · HighCorruption & state captureState capacity & governance5
4 · HighPublic procurement capabilityState capacity & governance6
3 · ModerateDeclining institutional trustInformation & trust7
3 · ModerateRegulatory capture & lobbying powerState capacity & governance8
3 · ModerateEntrenched opportunity inequalityPeople, health & work9
3 · ModerateLocal & city government capacityState capacity & governance11
3 · ModerateSocial protection coverage gapsState capacity & governance13
3 · ModerateErosion of rights & civic freedomsState capacity & governance14
3 · ModeratePolarisation & populismState capacity & governance15
3 · ModerateFiscal rules & budget credibilityState capacity & governance17
3 · ModerateResearch & development intensityPeople, health & work18
3 · ModerateTechnical & occupational skill shortagesPeople, health & work19
3 · ModerateIllicit finance & beneficial ownershipState capacity & governance20
3 · ModerateOfficial statistics & data capacityState capacity & governance21
3 · ModerateCivil unrest & protest mobilisationState capacity & governance25
3 · ModerateOutsourcing & public-private deliveryState capacity & governance27
3 · ModerateDigital public infrastructureState capacity & governance31
3 · ModerateAdaptive regulationState capacity & governance33
3 · ModerateData protection & digital rightsState capacity & governance44
3 · ModerateCitizen participation & deliberative democracyState capacity & governance60
3 · ModeratePublic-sector AI adoptionState capacity & governance75
3 · ModerateInformal employment persistencePeople, health & work84
3 · ModerateBusiness dynamism & start-up formationPeople, health & work85
3 · ModerateAlgorithmic accountability & biasState capacity & governance135