The transparency paradox: why do corrupt countries join EITI

Rules that require actors to make their finances transparent have become a key part of the anti-corruption toolkit, under the assumption that sunlight is the best disinfectant. This logic underpinned the creation, in 2002, of the Extractive Industries Transparency Initiative (EITI), an international club aimed at reducing corruption in oil, gas and mining. The initiative has proved popular, with 16 countries now EITI compliant and 23 others having achieved candidate status. However, as a soft law standard to which countries voluntarily commit, EITI presents a paradox: why would corrupt governments voluntarily expose themselves to sunlight? Does its popularity imply that it is meaningless? We argue that governments join because they are concerned about their reputation with international donors and expect to be rewarded by increased aid. Our quantitative analysis demonstrates that countries do gain access to increased aid the further they progress through the EITI implementation process. However, we also find that EITI achieves real results in terms of reducing corruption. We suggest that this is because EITI requires countries to build multi-stakeholder institutions which improve accountability, and provide qualitative evidence about how this has worked in several countries

The odds ratio for the BAL recovery rate failure was analysed using Pearson’s chi-squared test.

(DOCX)</p

Correlation with the recovery rate of bronchoalveolar lavage fluid.

(DOCX)</p

Factors affecting the recovery rate of BAL.

Factors affecting the recovery rate of BAL.</p

Flowchart of the study.

BAL bronchoalveolar lavage fluid.</p

S1 Fig -

The area of the bronchial wall did not show significant relationships with COPD (having COPD 13.8 mm2 [11.2–15.3] vs. no COPD 14.2 mm2 [10.9–15.3], p = 0.456) in S1A Fig, a target site of BAL (middle/lingual lobe 14.1 mm2 [10.9–18.5] vs. other lobes 14.3 mm2 [11.6–22.7], p = 0.241) in S1B Fig, sex (male 13.8 mm2 [10.4–17.6] vs. female 14.8 mm2 [11.3–19.2], p = 0.169) in S1C Fig, and age (>71 years old median 14.1 mm2 [10.6–19.1] vs. ≤71 years old median 14.2 mm2 [11.2–18.6], p = 0.877) in S1D Fig. (TIF)</p

Comparisons between the failure group and the success group.

Comparisons between the failure group and the success group.</p

A 3D image analysis system using a SYNAPSE VINCENT volume analyser calculated the area of the bronchial wall and bronchial lumen based on the lung analysis (A), lung volume affiliated bronchus in which BAL was performed based on the lung resection analysis (B), and bifurcation numbers of bronchus based on bronchoscopy simulator (C).

A 3D image analysis system using a SYNAPSE VINCENT volume analyser calculated the area of the bronchial wall and bronchial lumen based on the lung analysis (A), lung volume affiliated bronchus in which BAL was performed based on the lung resection analysis (B), and bifurcation numbers of bronchus based on bronchoscopy simulator (C).</p

Binomial logistic regression analysis of the predictive factors for the BAL recovery rate failure.

Binomial logistic regression analysis of the predictive factors for the BAL recovery rate failure.</p

ROC of the area of the bronchial wall for predicting BAL recovery rate failure.

The AUC was 0.673 (95% CI 0.572 to 0.775). The cut off value, which was decided by a point of maximum sensitivity and specificity, was 10.6 mm2. ROC: receiver operating characteristic curve, AUC: area under the curve, Cl: confidence interval.</p