evidoria

What works in Vilnius

All catalogues · Lithuania profile

19
evaluated practices
62/100
average quality score
0%
strong evidence, of 19 assessed
{# KAN-370: every section closes with a one-line "what is this number" note + Know more. The note only names metrics actually shown — the strong-evidence tile hides when nothing is assessed (KAN-364 honesty rule), so its mention hides with it. #}

Quality scores are 0–100 rubric scores; “strong evidence” reflects study design; adoptions count documented replications elsewhere. Know more

Evidence snapshot for Vilnius

Vilnius' talent-attraction strategy combines bold, targeted marketing campaigns with relocation infrastructure, with International House Vilnius serving approximately 1,300 people monthly. The city's development agency, Go Vilnius, has run insight-led campaigns since 2018, most notably the 2022 "Got fired by Meta or Twitter? Move to Vilnius" initiative aimed at global tech talent. However, the available evidence is limited to campaign reach and relocation-centre usage; the practices do not quantify actual talent retention, employment outcomes, or economic impact of these efforts.

Drawn from: LitAI State Data Lake — Lithuania's national AI-powered government data platform · Public Library Innovation Programme · GovTech Lab Lithuania — National AI Sandbox for Public Services · “Move to Vilnius” talent campaigns + International House Vilnius · Libraries for Innovation 2 · www.epilietis.eu - Lithuania’s e-Citizen · Digital skills for engineering industry · STT's Machine-Learning Risk Model for Public-Procurement Fraud and Corruption

Generated from this place's cited practices only. Always check the linked sources.

Strengths & weaknesses vs peers

{# KAN-369 chips show whole points; the explanation lives in the section's bottom note (KAN-370) so each concept is explained exactly once. #}

Strengths

Carbon — sequestration / storage, evidenced +32 pts 67 here · 35 average

Documented learning +27 pts 100 here · 73 average

Demonstrated reach +25 pts 100 here · 75 average

Curator validation +25 pts 100 here · 75 average

Effectiveness +19 pts 100 here · 81 average

Evaluated outcomes +16 pts 100 here · 84 average

Innovation level +15 pts 79 here · 64 average

Biodiversity — conservation / improvement, evidenced +14 pts 67 here · 53 average

Governance, capability & sustainability +14 pts 80 here · 66 average

Transparency, fairness & accountability +13 pts 67 here · 54 average

Teacher capability & pedagogy +11 pts 50 here · 39 average

Multi-stakeholder collaboration +10 pts 89 here · 78 average

Gender-mainstreaming embedding +10 pts 100 here · 90 average

Weaknesses

Fire resilience — risk reduction, evidenced -9 pts 0 here · 9 average

Transparency, ethics & data protection -17 pts 33 here · 50 average

Water & soil — retention, infiltration, erosion control -18 pts 33 here · 51 average

Evidence of learning impact -30 pts 0 here · 30 average

Evaluation evidence -36 pts 0 here · 36 average

{# Score profile vs peers (KAN-364, UX2.3): every dimension as place-vs-corpus bars — the full picture behind the strengths/weaknesses shortlists above. #}

Score profile vs peers

Carbon — sequestration / storage, evidenced
67 · 35
Documented learning
100 · 73
Demonstrated reach
100 · 75
Curator validation
100 · 75
Effectiveness
100 · 81
Evaluated outcomes
100 · 84
Innovation level
79 · 64
Biodiversity — conservation / improvement, evidenced
67 · 53
Governance, capability & sustainability
80 · 66
Transparency, fairness & accountability
67 · 54
Teacher capability & pedagogy
50 · 39
Multi-stakeholder collaboration
89 · 78
Gender-mainstreaming embedding
100 · 90
Achievement / evidence
100 · 93
Sustainability
85 · 80
Transferability / replicability
63 · 59
Inclusiveness / equity
44 · 41
Scalability
63 · 66
Equity & inclusion
50 · 54
Evidence of impact / measured results
52 · 60
Fire resilience — risk reduction, evidenced
0 · 9
Transparency, ethics & data protection
33 · 50
Water & soil — retention, infiltration, erosion control
33 · 51
Evidence of learning impact
0 · 30
Evaluation evidence
0 · 36

Coloured bar: Vilnius. Grey bar: peer average across the corpus. Both on a common 0–100 scale.

Points compare this place's average on each dimension with the average across all evaluated places, on a common 0–100 scale. Know more

Top good practices here

LitAI State Data Lake — Lithuania's national AI-powered government data platform · 87

Public Library Innovation Programme · 80

GovTech Lab Lithuania — National AI Sandbox for Public Services · 76

“Move to Vilnius” talent campaigns + International House Vilnius · 76

Libraries for Innovation 2 · 76

www.epilietis.eu - Lithuania’s e-Citizen · 76

Digital skills for engineering industry · 76

STT's Machine-Learning Risk Model for Public-Procurement Fraud and Corruption · 73

Each number is the practice's overall 0–100 quality score against its catalogue's rubric. Know more

Recommended to adopt or replicate

Transferable practices from elsewhere that address this place's gaps.

{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Digital Green — Video-Mediated Agricultural Extension · fit 100/100

  • Backed by strong evidence
  • Addresses this place's weak dimensions
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Kartu Prakerja – National Digital Skills and Financial Inclusion Programme · fit 100/100

  • Backed by strong evidence
  • Addresses this place's weak dimensions
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Liga Inan – Mobile Maternal Health Messaging Network · fit 89/100

  • Matches your scale
  • Backed by strong evidence
  • Addresses this place's weak dimensions
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Ciudad Mujer — El Salvador's Integrated Women's Services Programme · fit 100/100

  • Rated highly transferable
  • Backed by strong evidence
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

SASA! Community Mobilisation Programme against Intimate Partner Violence — Uganda · fit 100/100

  • Rated highly transferable
  • Backed by strong evidence
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Rwanda's Land Tenure Regularization Programme — Titling Land in Women's Names · fit 90/100

  • Rated highly transferable
  • Backed by strong evidence
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Sweden's Barnahus (Children's House) — Multidisciplinary One-Stop Centres for Child Victims of Sexual Abuse and Violence · fit 90/100

  • Rated highly transferable
  • Backed by strong evidence
{# KAN-369: display the true 0–100 fit (rec.score) — gap_score is ordering-only and exceeds 100 by construction; the weak-gap boost surfaces as a reason line instead. #}

Copenhagen Business Hub (Erhvervshus Hovedstaden) · fit 90/100

  • Rated highly transferable
  • Backed by strong evidence

Fit estimates how well a practice matches this place, 0 (poor) to 100 (excellent); the list is ordered to favour practices that address this place's gaps. Know more