What is Bangladesh's governance fairness score?

Bangladesh scored an Overall Fairness Index (OFI) of 1.74 out of 5.0 in the CARO Fairness Index V1 Pilot conducted in April 2026. Every domain scored below 2.0: Governance & Leadership (1.70), Justice & Rule of Law (1.81), Economy & Resources (1.88), Public Services & Welfare (1.44), and Accountability & Institutions (1.85). A score below 2.5 indicates majority perceived structural unfairness. This is the first citizen-administered, empirically governed measurement of structural governance fairness in Bangladesh or any comparable transitional democracy.

What is the CARO Fairness Index?

The CARO Fairness Index (FI) is a 25-question empirical instrument measuring structural governance fairness from the citizen's perspective across five domains: Governance & Leadership, Justice & Rule of Law, Economy & Resources, Public Services & Welfare, and Accountability & Institutions. Each question uses a 1-to-5 Likert scale (1 = Completely Unfair, 5 = Completely Fair). The instrument is bilingual (English and Bangla), administered through the PlayerOne platform at playerone.carononprofit.org, and governed by a three-board independence structure — making it constitutionally independent of any government, funder, or political actor. It is developed by CARO (Care for Assets, Resources, and Obligations), a Washington D.C.-based 501(c)(3) nonprofit, EIN 33-2441689.

How was the Bangladesh Fairness Index pilot conducted?

The Fairness Index V1 Bangladesh Pilot was conducted in April 2026 by CARO's Global Governance Lab. 86 verified respondents completed the 25-question bilingual survey. Responses were individually verified via phone or email confirmation with duplicate detection. Demographic data was collected for each respondent including age, gender, location (urban/rural/semi-urban), education level, occupation, and prior civic participation. The survey was administered through Google Forms and the PlayerOne platform. All responses are anonymous; only aggregate data is published. The full methodology is documented in the Global Governance Lab and available at carononprofit.org.

Which domain of Bangladesh governance scored lowest?

Public Services & Welfare (D4) scored lowest at 1.44 out of 5.0, representing the strongest unfairness signal in the pilot. This indicates the broadest consensus among respondents that Bangladesh's public services system is structurally unfair. The five domain scores were: Public Services & Welfare (1.44), Governance & Leadership (1.70), Justice & Rule of Law (1.81), Accountability & Institutions (1.85), and Economy & Resources (1.88). All five domains fell below 2.0.

How does the Fairness Index differ from Freedom House, V-Dem, or the Corruption Perceptions Index?

The CARO Fairness Index differs from existing governance indices in three fundamental ways. First, it is citizen-administered: citizens complete the survey themselves rather than expert panels scoring countries from outside. Second, it measures structural fairness specifically — whether the governance system is architecturally designed to be fair — rather than freedom, democracy scores, or corruption perception alone. Third, it is constitutionally independent through a three-board governance structure (Question Review Board, Methodology Board, Rights Safeguard Board) that prevents any government, funder, or organization including CARO from controlling what it measures or what it finds. Freedom House, V-Dem, Transparency International CPI, and World Bank Governance Indicators are all produced by Western institutions using expert panels. None of them ask citizens what they experience structurally.

Who conducted the Fairness Index V1 Bangladesh research?

The Fairness Index V1 Bangladesh Pilot was conducted by CARO (Care for Assets, Resources, and Obligations), a Washington D.C.-based 501(c)(3) nonprofit, EIN 33-2441689. The principal investigator is A.N.M. Nuruddin, Founder and Chief Architect of CARO and author of Fairness as Foundation (SSRN #6632960). The research division is the Global Governance Lab (GGL), with Samia Sultana Ridi as Research Lead. The work has been independently recognized by scholars at Harvard Allen Lab (Danielle Allen, Paulius Yamin), Stanford HAI (Rob Reich), University of Pennsylvania (Rogers Smith), Northwestern University (Cristina Lafont), and University of Michigan (Elizabeth Anderson).

Is the Fairness Index data publicly available?

Yes. The Fairness Index V1 Bangladesh Pilot aggregate results are publicly available at carononprofit.org/fi-pilot-results.html. This includes all five domain scores, the Overall Fairness Index (OFI) of 1.74/5.0, all 25 survey questions in English and Bangla, and demographic breakdown of respondents. Individual response data is not published to protect respondent anonymity. A GGL empirical paper with full methodology and statistical analysis is in preparation, targeting peer review submission in Q3 2026 and open-access publication in Q4 2026.

How can I participate in the Fairness Index?

The Fairness Index V2 is administered through the PlayerOne platform at playerone.carononprofit.org. Any Bangladeshi citizen with a Google account can register and complete the survey at no cost. Participation is part of CARO's 7-stage civic development journey. Participants also contribute to the expanding national dataset that will scale from the V1 pilot (86 respondents) to 1,000+ verified respondents across all 8 divisions of Bangladesh under the V2 program.

CARO Fairness Index — Bangladesh Pilot Results

Section I — Overall Fairness Index

1.74 out of 5.0

Majority perceives governance as structurally unfair

An OFI of 1.74 places this cohort in the Majority Unfair range (1.81–2.60 threshold), approaching the Strong Unfairness Consensus boundary (below 1.80). Across all five governance domains, participants consistently judged prevailing practices as falling short of structural fairness standards — no domain scored above 1.89.

The near-alignment of OFI (1.74) with the average institutional trust score (1.88) is consistent with Equitism’s theoretical prediction: populations perceiving high governance unfairness show proportionally low system trust.

OFI = 1.74 / 5.00 Institutional trust = 1.88 / 5.00 Scale: 1 = Completely Unfair → 5 = Completely Fair N = 86 valid responses

Key Findings

OFI of 1.74 is the first empirical data point in CARO’s longitudinal governance fairness tracking series. It establishes the Bangladesh baseline against which all future cohort measurements will be compared.
Near-alignment of OFI (1.74) and institutional trust (1.88) confirms Equitism’s theoretical prediction that populations perceiving high governance unfairness show proportionally low system trust.
Cohort profile: 71% aged 18–25, 54% undergraduate, 62% urban. Analytically significant youth-educated-urban signal — not yet nationally representative. All findings should be understood in that context.
All five domain scores fall below 2.0. This is not concentrated unfairness in one area — it is a broad, consistent signal across governance, justice, economy, public services, and accountability.

Section II — Domain Fairness Scores

Five domains.
All in the unfair range.

Domain Fairness Scores (DFS) computed using equal-weight averaging per Chapter 16 V1 formula: DFS(d) = (QFS_q1 + … + QFS_q5) / 5. All five scores fall below 2.0.

Governance Pentagon

Radar visualization. Inner boundary = 1.0. Outer boundary = 5.0. All five domains cluster near the unfair pole. Scale bars shown at 1, 2, 3, 4, 5.

Domain Score Breakdown

All five DFS values on the 1–5 structural fairness scale. Bar fill represents position within the 1–5 range. Every domain falls below 2.0.

D1 — Governance & Leadership 1.700

Strong unfairness consensus

D2 — Justice & Rule of Law 1.814

Majority perceives as unfair

D3 — Economy & Resources 1.877

Majority perceives as unfair

D4 — Public Services & Welfare 1.437

Strongest unfairness signal — lowest domain score

D5 — Accountability & Institutions 1.847

Majority perceives as unfair

Overall Fairness Index (OFI)

Equal-weight mean of five domain scores

1.74 / 5.00

Section III — Question Fairness Scores

All 25 questions.
Complete results.

QFS = mean of all valid responses per question. N = 86. σ = standard deviation. Bar represents position within the 1–5 range.

1.00–1.80: Strong unfairness consensus 1.81–2.60: Majority unfair 2.61–3.40: Contested

1

Governance & Leadership

1.700

Strong unfairness consensus

Q1

Is it fair for elected representatives to change political parties after being elected without returning to voters for a new mandate?নির্বাচিত প্রতিনিধিদের জন্য কি এটি ন্যায্য যে তারা নির্বাচিত হওয়ার পর ভোটারদের কাছ থেকে নতুন ম্যান্ডেট না নিয়ে রাজনৈতিক দল পরিবর্তন করতে পারেন?

1.86

σ 1.07

Majority unfair

Q2

Is it fair for governments to make major national decisions without publicly explaining the reasoning and evidence behind them?সরকারের জন্য কি এটি ন্যায্য যে তারা তাদের সিদ্ধান্তের পেছনের যুক্তি ও প্রমাণ জনসমক্ষে ব্যাখ্যা না করেই গুরুত্বপূর্ণ জাতীয় সিদ্ধান্ত গ্রহণ করে?

1.59

σ 1.14

Strong consensus

Q3

Is it fair for political leaders to appoint close family members to government positions?রাজনৈতিক নেতাদের জন্য কি এটি ন্যায্য যে তারা ঘনিষ্ঠ পারিবারিক সদস্যদের সরকারি পদে নিয়োগ দেন?

1.51

σ 1.08

Strong consensus

Q4

Is it fair for governments to restrict citizens’ right to public protest?সরকার কি নাগরিকদের প্রকাশ্যে প্রতিবাদ করার অধিকার সীমিত করতে পারে?

1.69

σ 1.14

Strong consensus

Q5

Is it fair for opposition parties to consistently block or reject government policies in order to gain political advantage, rather than on policy grounds?বিরোধী রাজনৈতিক দলগুলোর জন্য কি এটি ন্যায্য যে তারা নীতিগত ভিত্তির পরিবর্তে রাজনৈতিক সুবিধা অর্জনের লক্ষ্যে ধারাবাহিকভাবে সরকারি নীতিমালা বাধাগ্রস্ত বা প্রত্যাখ্যান করে?

1.85

σ 1.19

Majority unfair

2

Justice & Rule of Law

1.814

Majority perceives as unfair

Q6

Is it fair if wealthy individuals can access much better legal defense than ordinary citizens?ধনী ব্যক্তিরা কি সাধারণ নাগরিকদের তুলনায় অনেক ভালো আইনি সুরক্ষা পেতে পারেন?

1.43

σ 0.94

Strong consensus

Q7

Is it fair for governments to influence court decisions during politically sensitive cases?রাজনৈতিকভাবে সংবেদনশীল মামলায় আদালতের রায়কে প্রভাবিত করা সরকারের জন্য কি ন্যায্য?

1.54

σ 1.04

Strong consensus

Q8

Is it fair for people accused of crimes to remain detained for long periods without trial?অপরাধে অভিযুক্ত ব্যক্তিদের কি বিচার ছাড়াই দীর্ঘ সময় ধরে আটক রাখা ন্যায্য?

1.63

σ 0.96

Strong consensus

Q9

Is it fair for law enforcement to use physical force against protesters, even when some protesters have caused property damage?যখন কিছু প্রতিবাদকারী সম্পত্তির ক্ষতি করে, তখনও কি আইনশৃঙ্খলা রক্ষাকারী বাহিনীর জন্য প্রতিবাদকারীদের বিরুদ্ধে শারীরিক বলপ্রয়োগ করা যুক্তিসঙ্গত বা গ্রহণযোগ্য?

2.80

σ 1.53

Contested ⚠

Q10

Is it fair for public officials accused of corruption to remain in office during investigation?দুর্নীতির অভিযোগে অভিযুক্ত সরকারি কর্মকর্তারা কি তদন্ত চলাকালীন পদে থাকতে পারেন?

1.67

σ 1.15

Strong consensus

3

Economy & Resources

1.877

Majority perceives as unfair

Q11

Is it fair for very wealthy individuals to pay the same percentage of tax as low-income citizens?অত্যন্ত ধনী ব্যক্তিদের জন্য কি স্বল্প আয়ের নাগরিকদের মতো একই হারে কর প্রদান করা যুক্তিসঙ্গত?

1.59

σ 1.16

Strong consensus

Q12

Is it fair for governments to provide financial subsidies to large corporations?বড় কর্পোরেশনগুলোকে সরকার আর্থিক ভর্তুকি প্রদান করা কি ন্যায্য?

2.12

σ 1.24

Majority unfair

Q13

Is it fair for essential goods like food, medicine, and energy to be controlled by a small number of companies?খাদ্য, ওষুধ ও জ্বালানির মতো অত্যাবশ্যকীয় পণ্যের নিয়ন্ত্রণ যদি অল্প কয়েকটি প্রতিষ্ঠানের হাতে কেন্দ্রীভূত থাকে, তা কি যুক্তিসঙ্গত?

1.55

σ 1.01

Strong consensus

Q14

Is it fair for governments to provide no financial support or retraining programs for workers who lose their jobs due to automation or technological change?প্রযুক্তিগত পরিবর্তনের কারণে চাকরি হারানো শ্রমিকদের জন্য সরকার কি কোনো আর্থিক সহায়তা বা পুনঃপ্রশিক্ষণ না দেওয়াটা ন্যায্য?

2.33

σ 1.68

Majority unfair ⚠

Q15

Is it fair for government contracts to be awarded without open competitive bidding?সরকারি চুক্তি উন্মুক্ত ও প্রতিযোগিতামূলক দরপত্র প্রক্রিয়া ব্যতীত প্রদান করা কতটা গ্রহণযোগ্য বা উপযুক্ত?

1.80

σ 1.12

Strong consensus

4

Public Services & Welfare

1.437

Lowest domain — strongest unfairness signal

Q16

Is it fair for citizens in rural areas to receive fewer public services than citizens in major cities?গ্রামীণ এলাকার নাগরিকরা কি প্রধান শহরের নাগরিকদের তুলনায় কম সরকারি সেবা পাবেন?

1.40

σ 0.83

Strong consensus

Q17

Is it fair for wealthier citizens to receive better healthcare simply because they can pay more?ধনী নাগরিকরা কি শুধু বেশি অর্থ দেওয়ার সক্ষমতার কারণে উন্নত স্বাস্থ্যসেবা পাবেন?

1.47

σ 0.85

Strong consensus

Q18

Is it fair for public education quality to differ significantly between regions?বিভিন্ন অঞ্চলে সরকারি শিক্ষার মানের মধ্যে কি উল্লেখযোগ্য পার্থক্য থাকা উচিত?

1.28

σ 0.78

Strongest ★

Q19

Is it fair for governments to prioritize large infrastructure projects while leaving basic social welfare programs underfunded?বৃহৎ অবকাঠামোগত প্রকল্পসমূহকে অগ্রাধিকার দিয়ে মৌলিক সামাজিক কল্যাণমূলক কর্মসূচিগুলোকে পর্যাপ্ত অর্থায়ন থেকে বঞ্চিত রাখা কি সরকারের পক্ষে ন্যায্য ও সমতাভিত্তিক নীতি হিসেবে বিবেচিত হতে পারে?

1.55

σ 0.84

Strong consensus

Q20

Is it fair for political connections to influence access to government services?রাজনৈতিক সংযোগের প্রভাবের মাধ্যমে সরকারি সেবাসমূহে প্রবেশাধিকার নির্ধারিত হওয়া কি ন্যায়সংগত ও সুশাসনের নীতির সঙ্গে সামঞ্জস্যপূর্ণ বলে বিবেচিত হতে পারে?

1.50

σ 0.97

Strong consensus

5

Accountability & Institutions

1.847

Majority perceives as unfair

Q21

Is it fair for governments to limit access to information about public spending?সরকারের ক্ষেত্রে জনসাধারণের ব্যয়সংক্রান্ত তথ্যের প্রবেশাধিকার সীমিত করা কতটা গ্রহণযোগ্য ও ন্যায়সঙ্গত?

2.24

σ 1.33

Majority unfair

Q22

Is it fair for media organizations to support specific political parties openly?মিডিয়া প্রতিষ্ঠানগুলো কি প্রকাশ্যে নির্দিষ্ট রাজনৈতিক দলকে সমর্থন করতে পারে?

1.49

σ 0.97

Strong consensus

Q23

Is it fair for governments to use emergency powers to restrict citizens’ freedoms?সরকার কি জরুরি ক্ষমতা ব্যবহার করে নাগরিকদের স্বাধীনতা সীমিত করতে পারে?

1.78

σ 1.12

Strong consensus

Q24

Is it fair for powerful corporations to influence government policies through lobbying?বৃহৎ কর্পোরেট প্রতিষ্ঠানের লবিং কার্যক্রমের মাধ্যমে রাষ্ট্রের নীতি প্রণয়নে প্রভাব বিস্তার করা কতটা যৌক্তিক ও গ্রহণযোগ্য?

1.49

σ 0.84

Strong consensus

Q25

Is it fair for international organizations to attach policy conditions to financial aid provided to a country?আন্তর্জাতিক সংস্থাগুলো কি কোনো দেশে আর্থিক সাহায্যের সাথে নীতিগত শর্ত আরোপ করতে পারে?

2.23

σ 1.39

Majority unfair

Section IV — Analytical Highlights

What the data
shows most clearly.

Strongest Consensus — Unfair

Q18 — Education quality by region

“Is it fair for public education quality to differ significantly between regions?”

1.28

Lowest QFS across all 25 questions. σ = 0.78. Near-unanimous rejection — the tightest consensus in the dataset.

Only Contested Question

Q9 — Pre-trial detention

“Is it fair for people accused of crimes to be detained for long periods without trial?”

2.80

Highest QFS. Only question crossing the contested threshold (2.61–3.40). Highest σ = 1.53 — maximum disagreement.

Most Divided Response

Q14 — Contracts without competitive bidding

“Is it fair for government contracts to be awarded without open competitive bidding?”

2.33

Highest standard deviation in the dataset: σ = 1.68. Responses spread across the full 1–5 range.

Weakest Domain (Most Unfair)

D4 — Public Services & Welfare

Rural/urban service disparity, wealth-based healthcare, regional education inequality — all strongly rejected.

1.44

Lowest domain score. All five questions in this domain score below 1.55. Strongest unfairness signal across all five domains.

Complete Domain & OFI Summary

Domain	DFS Score	Interpretation	Lowest Q	Highest Q
D1 Governance & Leadership	1.700	Strong unfairness consensus	Q3 — 1.51 (Nepotism)	Q1 — 1.86 (Party switching)
D2 Justice & Rule of Law	1.814	Majority unfair	Q6 — 1.43 (Legal defense)	Q9 — 2.80 (Pre-trial detention)
D3 Economy & Resources	1.877	Majority unfair	Q11 — 1.59 (Corruption in office)	Q14 — 2.33 (No competitive bidding)
D4 Public Services & Welfare	1.437	★ Strongest unfairness signal	Q18 — 1.28 (Education quality)	Q19 — 1.55 (Infrastructure vs welfare)
D5 Accountability & Institutions	1.847	Majority unfair	Q22 — 1.49 (Media partisanship)	Q21 — 2.24 (Spending opacity)
Overall Fairness Index (OFI)	1.74	Majority Unfair range — approaching Strong Unfairness Consensus threshold (1.80) — N=86 — Bangladesh Pilot April 2026

Section V — Participant Profile

Who responded.
N = 86 valid responses.

Age Group

18–2571%

26–3524%

Under 182%

Over 501%

Gender

Male61%

Female37%

Prefer not to say1%

Location

Urban / Major city62%

Semi-urban / Town21%

Rural / Village15%

Prefer not to say1%

Education

Undergraduate / Bachelor's54%

Higher secondary / A-level30%

Postgraduate / Master's+14%

Secondary / High school1%

⚠

Cohort limitation. This pilot is not nationally representative. It skews young (71% aged 18–25), male (61%), urban (62%), and educated (54% undergraduate or above). The OFI of 1.74 reflects this cohort’s structural fairness perceptions. GGL publications will contextualize findings within the participant demographic profile and track how scores shift as the sample expands and diversifies across age, location, gender, and education cohorts.

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Responses are anonymous · Aggregate data published by Global Governance Lab · Publication: June 2026

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The BangladeshFairness PerceptionBaseline

Majority perceives governance as structurally unfair

Majority perceives governance as structurally unfair

Key Findings

Five domains.All in the unfair range.

Governance Pentagon

Domain Score Breakdown

All 25 questions.Complete results.

What the datashows most clearly.

Who responded.N = 86 valid responses.

Age Group

Gender

Location

Education

Add your voice to theglobal measurement.

86 verified voices.Help us reach 1,000.

The Bangladesh
Fairness Perception
Baseline

Five domains.
All in the unfair range.

All 25 questions.
Complete results.

What the data
shows most clearly.

Who responded.
N = 86 valid responses.

Add your voice to the
global measurement.

86 verified voices.
Help us reach 1,000.