evidoria

What works in Moscow

All catalogues · Russia profile

4
evaluated practices
37/100
average quality score
0%
strong evidence, of 4 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 Moscow

Moscow's AI Facial-Recognition Camera Network — From Traffic Safety Pitch to Dissident and Draft-Evader Tracking shows that Moscow connected roughly 230,000 AI facial-recognition cameras, initially presented as a traffic-safety measure but subsequently deployed to track dissidents and draft evaders. The practice entry indicates this represents a shift from stated public-safety aims to surveillance of political opposition and military conscription enforcement, though the summary provided in the CONTEXT block is truncated and does not give complete details on outcomes or scale beyond the camera count.

Drawn from: Azbuka Interneta: Digital Literacy for Russian Pensioners · AI Challenge & the Russian AI Olympiad — Sber's School-to-University AI Talent Pipeline · Maternity Capital — Russia's Cash-for-Births Policy and Its Gender-Equality Blind Spot · Moscow's AI Facial-Recognition Camera Network — From Traffic Safety Pitch to Dissident and Draft-Evader Tracking

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

Evaluation evidence +64 pts 100 here · 36 average

Demonstrated reach +25 pts 100 here · 75 average

Sustainability (ongoing) +20 pts 100 here · 80 average

Evaluated outcomes +16 pts 100 here · 84 average

Weaknesses

Scalability beyond pilot -16 pts 50 here · 66 average

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

Equity & inclusion -21 pts 33 here · 54 average

Innovation level -24 pts 40 here · 64 average

Transferability / replicability -26 pts 33 here · 59 average

Evidence of impact / measured public value -27 pts 33 here · 60 average

Teacher capability & pedagogy -39 pts 0 here · 39 average

Efficiency -52 pts 0 here · 52 average

Transparency, fairness & accountability -54 pts 0 here · 54 average

Governance, capability & sustainability -66 pts 0 here · 66 average

Documented learning -73 pts 0 here · 73 average

Curator validation -75 pts 0 here · 75 average

Effectiveness -81 pts 0 here · 81 average

Impact on gender equality -83 pts 0 here · 83 average

Gender-mainstreaming embedding -90 pts 0 here · 90 average

Achievement / evidence -93 pts 0 here · 93 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

Evaluation evidence
100 · 36
Demonstrated reach
100 · 75
Sustainability (ongoing)
100 · 80
Evaluated outcomes
100 · 84
Evidence of learning impact
33 · 30
Scalability beyond pilot
50 · 66
Transparency, ethics & data protection
33 · 50
Equity & inclusion
33 · 54
Innovation level
40 · 64
Transferability / replicability
33 · 59
Evidence of impact / measured public value
33 · 60
Teacher capability & pedagogy
0 · 39
Efficiency
0 · 52
Transparency, fairness & accountability
0 · 54
Governance, capability & sustainability
0 · 66
Documented learning
0 · 73
Curator validation
0 · 75
Effectiveness
0 · 81
Impact on gender equality
0 · 83
Gender-mainstreaming embedding
0 · 90
Achievement / evidence
0 · 93

Coloured bar: Moscow. 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

Azbuka Interneta: Digital Literacy for Russian Pensioners · 68

AI Challenge & the Russian AI Olympiad — Sber's School-to-University AI Talent Pipeline · 33

Maternity Capital — Russia's Cash-for-Births Policy and Its Gender-Equality Blind Spot · 26

Moscow's AI Facial-Recognition Camera Network — From Traffic Safety Pitch to Dissident and Draft-Evader Tracking · 20

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. #}

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

  • Rated highly transferable
  • 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. #}

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

  • Rated highly transferable
  • 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. #}

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. #}

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

  • Rated highly transferable
  • 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. #}

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
  • 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. #}

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

  • Rated highly transferable
  • 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. #}

Stadtidee Aarau — Switzerland's First City-Wide Participatory Budget Using the Method of Equal Shares · fit 90/100

  • Rated highly transferable
  • Backed by strong evidence
  • Addresses this place's weak dimensions

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