HomeFairness IndexBangladesh Pilot Results — April 2026
●  Global Governance Lab  ·  Bangladesh Pilot  ·  April 2026

The Bangladesh
Fairness Perception
Baseline

The first empirical measurement of structural governance fairness as collectively perceived by participants — across five governance domains. This is CARO Fairness Index Version 1.

86
Valid consented
responses
1.74/5
Overall Fairness
Index (OFI)
25
Questions · 5
governance domains
1.88/5
Avg. institutional
trust score
Overall Fairness Index
Bangladesh Pilot V1 — April 2026
1.74 / 5.0

Majority perceives governance as structurally unfair

All five domains below 2.0 — consistent signal across the full cohort.

Governance & Leadership1.70
Justice & Rule of Law1.81
Economy & Resources1.88
Public Services & Welfare1.44
Accountability & Institutions1.85
See full domain analysis ↓
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 Strong Unfairness Consensus range (1.00–1.80), at the upper boundary of that range. 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 13 V1 formula: DFS(d) = (QFSq1 + … + QFSq5) / 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.

5 4 3 2 1 1.70 1.81 1.88 1.44 1.85 Governance & Leadership Justice & Rule of Law Economy & Resources Public Services & Welfare Accountability & Institutions

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?
1.53
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 — Force against protesters
“Is it fair for law enforcement to use physical force against protesters, even when some protesters have caused property damage?”
2.80
Highest QFS. Only question crossing the contested threshold (2.61–3.40). Highest σ = 1.53 — maximum disagreement.
Most Divided Response
Q14 — Automation retraining
“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?”
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 (Force against protesters)
D3 Economy & Resources 1.877 Majority unfair Q11 — 1.59 (Corruption in office) Q14 — 2.33 (Automation retraining)
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 Strong Unfairness Consensus range (1.00–1.80) — N=86 — Bangladesh Pilot April 2026
See full score calculations ↓
Section V — Score Calculations

How the scores
were calculated.

Every number on this page is reproducible from the raw responses. This section shows the full calculation chain — from individual responses to Question Fairness Scores, Domain Fairness Scores, and the Overall Fairness Index — step by step, per Chapter 13 of Fairness as Foundation (SSRN #6632960).

Formula Definitions — Chapter 13
QFS — Question Fairness Score
QFS(q) = Σ responses / N
Arithmetic mean of all valid responses to a question. N = 86 for all questions in this pilot.
DFS — Domain Fairness Score
DFS(d) = (QFSq1 + … + QFSq5) / 5
Equal-weight average of the five QFS values within each domain. V1 pilot formula.
OFI — Overall Fairness Index
OFI = (D1 + D2 + D3 + D4 + D5) / 5
Equal-weight average of the five domain scores. Rounded to 2 decimal places at each stage.
Scale
1.00–1.80  Strong unfairness consensus
1.81–2.60  Majority unfair
2.61–3.40  Contested
3.41–4.20  Mostly fair
4.21–5.00  Strongly fair

V1 pilot scope: The full Fairness Index scoring system (Chapter 13) also defines a Question Confidence Score (QCS = 1 − σ/2.0), Question Participation Score (QPS), and Adjusted Question Fairness Score (AQFS = QFS × (0.60 + 0.20 × QCS + 0.20 × QPS)). These are not calculated in this pilot. The pilot uses the simplified equal-weight mean method — QFS → DFS → OFI — consistent with the book's explicit statement that equal weights apply in the pilot phase. QCS, QPS, and AQFS will be incorporated in the formal V1 launch once a target sample threshold is defined. V1 (30 questions — current 25 plus 5 BD transition-specific questions drafted by the FI Academic Advisory Panel) launches following panel review and finalization within the NED grant period. V2 follows at full scale: 50 questions, 7 domains, 1,000+ respondents. The σ values published here are the raw inputs from which QCS would be derived.

D1 Governance & Leadership
Q1

Is it fair for elected representatives to change political parties after being elected without returning to voters for a new mandate?

1.86
σ = 1.06
Response distribution (N=86)
46
1
14
2
19
3
6
4
1
5
QFS(Q1) = ((1×46) + (2×14) + (3×19) + (4×6) + (5×1)) ÷ 86
= 46 + 28 + 57 + 24 + 5
= 160 ÷ 86
= 1.8605  Majority unfair
Q2

Is it fair for governments to make major national decisions without publicly explaining the reasoning and evidence behind them?

1.59
σ = 1.14
Response distribution (N=86)
62
1
9
2
9
3
0
4
6
5
QFS(Q2) = ((1×62) + (2×9) + (3×9) + (5×6)) ÷ 86
= 62 + 18 + 27 + 30
= 137 ÷ 86
= 1.593  Strong unfairness consensus
Q3

Is it fair for political leaders to appoint close family members to government positions?

1.51
σ = 1.08
Response distribution (N=86)
65
1
9
2
6
3
1
4
5
5
QFS(Q3) = ((1×65) + (2×9) + (3×6) + (4×1) + (5×5)) ÷ 86
= 65 + 18 + 18 + 4 + 25
= 130 ÷ 86
= 1.5116  Strong unfairness consensus
Q4

Is it fair for governments to restrict citizens' right to public protest?

1.69
σ = 1.14
Response distribution (N=86)
56
1
13
2
10
3
2
4
5
5
QFS(Q4) = ((1×56) + (2×13) + (3×10) + (4×2) + (5×5)) ÷ 86
= 56 + 26 + 30 + 8 + 25
= 145 ÷ 86
= 1.686  Strong unfairness 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?

1.85
σ = 1.19
Response distribution (N=86)
49
1
15
2
13
3
4
4
5
5
QFS(Q5) = ((1×49) + (2×15) + (3×13) + (4×4) + (5×5)) ÷ 86
= 49 + 30 + 39 + 16 + 25
= 159 ÷ 86
= 1.8488  Majority unfair
DFS Calculation — D1
DFS(D1) = (1.8605 + 1.593 + 1.5116 + 1.686 + 1.8488) ÷ 5
           = 8.4999 ÷ 5
           = 1.7  → displayed as 1.7
D2 Justice & Rule of Law
Q6

Is it fair if wealthy individuals can access much better legal defense than ordinary citizens?

1.43
σ = 0.94
Response distribution (N=86)
66
1
10
2
6
3
1
4
3
5
QFS(Q6) = ((1×66) + (2×10) + (3×6) + (4×1) + (5×3)) ÷ 86
= 66 + 20 + 18 + 4 + 15
= 123 ÷ 86
= 1.4302  Strong unfairness consensus
Q7

Is it fair for governments to influence court decisions during politically sensitive cases?

1.53
σ = 1.04
Response distribution (N=86)
62
1
11
2
8
3
1
4
4
5
QFS(Q7) = ((1×62) + (2×11) + (3×8) + (4×1) + (5×4)) ÷ 86
= 62 + 22 + 24 + 4 + 20
= 132 ÷ 86
= 1.5349  Strong unfairness consensus
Q8

Is it fair for people accused of crimes to remain detained for long periods without trial?

1.63
σ = 0.96
Response distribution (N=86)
54
1
15
2
14
3
1
4
2
5
QFS(Q8) = ((1×54) + (2×15) + (3×14) + (4×1) + (5×2)) ÷ 86
= 54 + 30 + 42 + 4 + 10
= 140 ÷ 86
= 1.6279  Strong unfairness consensus
Q9

Is it fair for law enforcement to use physical force against protesters, even when some protesters have caused property damage?

2.8
σ = 1.52
Response distribution (N=86)
25
1
14
2
20
3
7
4
20
5
QFS(Q9) = ((1×25) + (2×14) + (3×20) + (4×7) + (5×20)) ÷ 86
= 25 + 28 + 60 + 28 + 100
= 241 ÷ 86
= 2.8023  Contested
Q10

Is it fair for public officials accused of corruption to remain in office during investigation?

1.67
σ = 1.15
Response distribution (N=86)
58
1
10
2
11
3
2
4
5
5
QFS(Q10) = ((1×58) + (2×10) + (3×11) + (4×2) + (5×5)) ÷ 86
= 58 + 20 + 33 + 8 + 25
= 144 ÷ 86
= 1.6744  Strong unfairness consensus
DFS Calculation — D2
DFS(D2) = (1.4302 + 1.5349 + 1.6279 + 2.8023 + 1.6744) ÷ 5
           = 9.0697 ÷ 5
           = 1.8139  → displayed as 1.81
D3 Economy & Resources
Q11

Is it fair for very wealthy individuals to pay the same percentage of tax as low-income citizens?

1.59
σ = 1.16
Response distribution (N=86)
62
1
11
2
5
3
2
4
6
5
QFS(Q11) = ((1×62) + (2×11) + (3×5) + (4×2) + (5×6)) ÷ 86
= 62 + 22 + 15 + 8 + 30
= 137 ÷ 86
= 1.593  Strong unfairness consensus
Q12

Is it fair for governments to provide financial subsidies to large corporations?

2.12
σ = 1.24
Response distribution (N=86)
38
1
17
2
20
3
5
4
6
5
QFS(Q12) = ((1×38) + (2×17) + (3×20) + (4×5) + (5×6)) ÷ 86
= 38 + 34 + 60 + 20 + 30
= 182 ÷ 86
= 2.1163  Majority unfair
Q13

Is it fair for essential goods like food, medicine, and energy to be controlled by a small number of companies?

1.55
σ = 1.01
Response distribution (N=86)
61
1
11
2
9
3
2
4
3
5
QFS(Q13) = ((1×61) + (2×11) + (3×9) + (4×2) + (5×3)) ÷ 86
= 61 + 22 + 27 + 8 + 15
= 133 ÷ 86
= 1.5465  Strong unfairness 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?

2.33
σ = 1.68
Response distribution (N=86)
46
1
10
2
6
3
4
4
20
5
QFS(Q14) = ((1×46) + (2×10) + (3×6) + (4×4) + (5×20)) ÷ 86
= 46 + 20 + 18 + 16 + 100
= 200 ÷ 86
= 2.3256  Majority unfair
Q15

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

1.8
σ = 1.11
Response distribution (N=86)
49
1
16
2
13
3
5
4
3
5
QFS(Q15) = ((1×49) + (2×16) + (3×13) + (4×5) + (5×3)) ÷ 86
= 49 + 32 + 39 + 20 + 15
= 155 ÷ 86
= 1.8023  Majority unfair
DFS Calculation — D3
DFS(D3) = (1.593 + 2.1163 + 1.5465 + 2.3256 + 1.8023) ÷ 5
           = 9.3837 ÷ 5
           = 1.8767  → displayed as 1.88
D4 Public Services & Welfare
Q16

Is it fair for citizens in rural areas to receive fewer public services than citizens in major cities?

1.4
σ = 0.83
Response distribution (N=86)
65
1
12
2
7
3
0
4
2
5
QFS(Q16) = ((1×65) + (2×12) + (3×7) + (5×2)) ÷ 86
= 65 + 24 + 21 + 10
= 120 ÷ 86
= 1.3953  Strong unfairness consensus
Q17

Is it fair for wealthier citizens to receive better healthcare simply because they can pay more?

1.47
σ = 0.85
Response distribution (N=86)
61
1
14
2
8
3
2
4
1
5
QFS(Q17) = ((1×61) + (2×14) + (3×8) + (4×2) + (5×1)) ÷ 86
= 61 + 28 + 24 + 8 + 5
= 126 ÷ 86
= 1.4651  Strong unfairness consensus
Q18

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

1.28
σ = 0.78
Response distribution (N=86)
73
1
6
2
5
3
0
4
2
5
QFS(Q18) = ((1×73) + (2×6) + (3×5) + (5×2)) ÷ 86
= 73 + 12 + 15 + 10
= 110 ÷ 86
= 1.2791  Strong unfairness consensus
Q19

Is it fair for governments to prioritize large infrastructure projects while leaving basic social welfare programs underfunded?

1.55
σ = 0.84
Response distribution (N=86)
55
1
17
2
13
3
0
4
1
5
QFS(Q19) = ((1×55) + (2×17) + (3×13) + (5×1)) ÷ 86
= 55 + 34 + 39 + 5
= 133 ÷ 86
= 1.5465  Strong unfairness consensus
Q20

Is it fair for political connections to influence access to government services?

1.5
σ = 0.97
Response distribution (N=86)
63
1
9
2
11
3
0
4
3
5
QFS(Q20) = ((1×63) + (2×9) + (3×11) + (5×3)) ÷ 86
= 63 + 18 + 33 + 15
= 129 ÷ 86
= 1.5  Strong unfairness consensus
DFS Calculation — D4
DFS(D4) = (1.3953 + 1.4651 + 1.2791 + 1.5465 + 1.5) ÷ 5
           = 7.186 ÷ 5
           = 1.4372  → displayed as 1.44
D5 Accountability & Institutions
Q21

Is it fair for governments to limit access to information about public spending?

2.24
σ = 1.33
Response distribution (N=86)
34
1
20
2
19
3
3
4
10
5
QFS(Q21) = ((1×34) + (2×20) + (3×19) + (4×3) + (5×10)) ÷ 86
= 34 + 40 + 57 + 12 + 50
= 193 ÷ 86
= 2.2442  Majority unfair
Q22

Is it fair for media organizations to support specific political parties openly?

1.49
σ = 0.97
Response distribution (N=86)
65
1
6
2
11
3
2
4
2
5
QFS(Q22) = ((1×65) + (2×6) + (3×11) + (4×2) + (5×2)) ÷ 86
= 65 + 12 + 33 + 8 + 10
= 128 ÷ 86
= 1.4884  Strong unfairness consensus
Q23

Is it fair for governments to use emergency powers to restrict citizens' freedoms?

1.78
σ = 1.12
Response distribution (N=86)
50
1
15
2
16
3
0
4
5
5
QFS(Q23) = ((1×50) + (2×15) + (3×16) + (5×5)) ÷ 86
= 50 + 30 + 48 + 25
= 153 ÷ 86
= 1.7791  Strong unfairness consensus
Q24

Is it fair for powerful corporations to influence government policies through lobbying?

1.49
σ = 0.84
Response distribution (N=86)
58
1
18
2
7
3
2
4
1
5
QFS(Q24) = ((1×58) + (2×18) + (3×7) + (4×2) + (5×1)) ÷ 86
= 58 + 36 + 21 + 8 + 5
= 128 ÷ 86
= 1.4884  Strong unfairness consensus
Q25

Is it fair for international organizations to attach policy conditions to financial aid provided to a country?

2.23
σ = 1.39
Response distribution (N=86)
39
1
15
2
13
3
11
4
8
5
QFS(Q25) = ((1×39) + (2×15) + (3×13) + (4×11) + (5×8)) ÷ 86
= 39 + 30 + 39 + 44 + 40
= 192 ÷ 86
= 2.2326  Majority unfair
DFS Calculation — D5
DFS(D5) = (2.2442 + 1.4884 + 1.7791 + 1.4884 + 2.2326) ÷ 5
           = 9.2327 ÷ 5
           = 1.8465  → displayed as 1.85
Overall Fairness Index — Final Calculation

The OFI is the equal-weight average of the five domain scores. Each domain score is the equal-weight average of its five questions. All scores rounded to 2 decimal places at each stage before the next calculation — consistent with the Chapter 13 V1 pilot methodology.

D1
1.7
Governance & Leadership
D2
1.81
Justice & Rule of Law
D3
1.88
Economy & Resources
D4
1.44
Public Services & Welfare
D5
1.85
Accountability & Institutions
OFI = (1.7 + 1.81 + 1.88 + 1.44 + 1.85) ÷ 5
     = 8.68 ÷ 5
     = 1.7360
     = 1.74 (rounded to 2dp)
Rounding note: The raw unrounded OFI computes to 1.7349. Rounding domain scores to 2dp before averaging (as displayed on this page) produces 1.736, which rounds to 1.74. Both methods are consistent with the Chapter 13 V1 pilot formula. The published figure of 1.74 reflects the rounded-domain method, matching how scores are displayed throughout.
Q Question N Σ QFS σ Interpretation
D1 — Governance & Leadership
Q1 Is it fair for elected representatives to change political parties after be… 86 160 1.86 1.06 Majority unfair
Q2 Is it fair for governments to make major national decisions without publicl… 86 137 1.59 1.14 Strong unfairness consensus
Q3 Is it fair for political leaders to appoint close family members to governm… 86 130 1.51 1.08 Strong unfairness consensus
Q4 Is it fair for governments to restrict citizens' right to public protest? 86 145 1.69 1.14 Strong unfairness consensus
Q5 Is it fair for opposition parties to consistently block or reject governmen… 86 159 1.85 1.19 Majority unfair
D2 — Justice & Rule of Law
Q6 Is it fair if wealthy individuals can access much better legal defense than… 86 123 1.43 0.94 Strong unfairness consensus
Q7 Is it fair for governments to influence court decisions during politically … 86 132 1.53 1.04 Strong unfairness consensus
Q8 Is it fair for people accused of crimes to remain detained for long periods… 86 140 1.63 0.96 Strong unfairness consensus
Q9 Is it fair for law enforcement to use physical force against protesters, ev… 86 241 2.8 1.52 Contested
Q10 Is it fair for public officials accused of corruption to remain in office d… 86 144 1.67 1.15 Strong unfairness consensus
D3 — Economy & Resources
Q11 Is it fair for very wealthy individuals to pay the same percentage of tax a… 86 137 1.59 1.16 Strong unfairness consensus
Q12 Is it fair for governments to provide financial subsidies to large corporat… 86 182 2.12 1.24 Majority unfair
Q13 Is it fair for essential goods like food, medicine, and energy to be contro… 86 133 1.55 1.01 Strong unfairness consensus
Q14 Is it fair for governments to provide no financial support or retraining pr… 86 200 2.33 1.68 Majority unfair
Q15 Is it fair for government contracts to be awarded without open competitive … 86 155 1.8 1.11 Majority unfair
D4 — Public Services & Welfare
Q16 Is it fair for citizens in rural areas to receive fewer public services tha… 86 120 1.4 0.83 Strong unfairness consensus
Q17 Is it fair for wealthier citizens to receive better healthcare simply becau… 86 126 1.47 0.85 Strong unfairness consensus
Q18 Is it fair for public education quality to differ significantly between reg… 86 110 1.28 0.78 Strong unfairness consensus
Q19 Is it fair for governments to prioritize large infrastructure projects whil… 86 133 1.55 0.84 Strong unfairness consensus
Q20 Is it fair for political connections to influence access to government serv… 86 129 1.5 0.97 Strong unfairness consensus
D5 — Accountability & Institutions
Q21 Is it fair for governments to limit access to information about public spen… 86 193 2.24 1.33 Majority unfair
Q22 Is it fair for media organizations to support specific political parties op… 86 128 1.49 0.97 Strong unfairness consensus
Q23 Is it fair for governments to use emergency powers to restrict citizens' fr… 86 153 1.78 1.12 Strong unfairness consensus
Q24 Is it fair for powerful corporations to influence government policies throu… 86 128 1.49 0.84 Strong unfairness consensus
Q25 Is it fair for international organizations to attach policy conditions to f… 86 192 2.23 1.39 Majority unfair
Domain Q Sum ÷ 5 DFS Interpretation
D1 Governance & Leadership 8.4999 5 1.7 Strong unfairness consensus
D2 Justice & Rule of Law 9.0697 5 1.81 Majority unfair
D3 Economy & Resources 9.3837 5 1.88 Majority unfair
D4 Public Services & Welfare 7.186 5 1.44 Strong unfairness consensus
D5 Accountability & Institutions 9.2327 5 1.85 Majority unfair
OFI = (1.7 + 1.81 + 1.88 + 1.44 + 1.85) ÷ 5 = 8.68 ÷ 5 8.68 5 1.74 Strong Unfairness Consensus (1.00–1.80)

Raw data: playerone.carononprofit.org  ·  Methodology: Fairness as Foundation, Chapter 13 (SSRN #6632960)  ·  GGL empirical paper in peer review, target Q3 2026.

Section VI — 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.

Join the dataset

Add your voice to the
global measurement.

The Fairness Index survey is open globally through the PlayerOne platform. 25 questions. 5–8 minutes. Every response expands the empirical foundation of the world’s first governance fairness measurement.

Take the Fairness Index on PlayerOne → GGL Research & Publications →

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

Scale the measurement

86 verified voices.
Help us reach 1,000.

You just read Bangladesh's first governance fairness baseline. The next step is scaling it nationally — 1,000+ verified respondents across all 8 divisions. Every contribution funds one more verified voice.

Support the scale-up → Take the Fairness Index →
Related
Contribute to the next dataset
Take the FI on PlayerOne → About the Fairness Index → Global Governance Lab → PlayerOne platform →