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In the public sector, Training and Experience (T & E) exams assess prior experience and are one of the most often used methods for selecting job applicants. This study uses a KSA approach, where raters judge the quality of job relevant prior experience, not its duration or quantity. It was hypothesized that an additional rater and a consensus meeting between raters would increase reliability and validity.

T & E and supervisory ratings were obtained over a 12-year period for 166 candidates seeking promotion to a budget analyst position. Validity was measured by the correlation between T & E scores and supervisory ratings. Consensus was required only for T & E scores differing by a specific amount (hybrid consensus).

Intraclass reliability was 0.73, 0.84, and 0.95 in the one-rater, two-rater, and hybrid consensus conditions with each coefficient greater than the next (p < 0.05) showing the benefit of multiple raters and consensus for reliability. Validity was significant at 0.21, 0.26, and 0.251 for each rating condition, respectively (two-tail test; p < 0.01). Validity was greater in the two-rater condition than in the one-rater condition (one-tail test; p < 0.05). Consensus did not improve validity beyond that of two raters. For consensus T & Es (n=76), two raters improved validity (one-tail test; p < 0.05), moving from 0.112 to 0.231 but not reliability; consensus improved reliability (two-tail test; p < 0.05) but not validity.

There has been a vacuum in T & E research for close to 20 years. Validity data are difficult to obtain but critical for meta-analysis. T & Es showed validity. Use of two raters improved validity but consensus did not increase the gain.

This paper aims to investigate the extent of corruption globally, explains its social and economic consequences and introduces a model, composed of corporate governance mechanisms, internal controls and red flag analyses, which organizations can apply to prevent corruption.

This study uses criminology theories to analyze corruption and its prevention.

The global cost of bribery alone is estimated at US$1tn annually, not including costs resulting from non-completion and deficient completion of development projects (World Bank Institute, 2004). This paper shows that an effective prevention model should include a positive work environment and ethical governance; the implementation of a compliance risk management program with fraud risk assessments; an accessible psychological assistance program for employees; regular employee anti-fraud training; the implementation of targeted internal controls such as proper segregation of organizational duties; the adoption of fair compensation levels and realistic individual performance goals; a user-friendly and anonymous reporting mechanism; and independent and regular analyses of abnormal patterns (red flags).

This paper extends previous research by tying together disparate factors into a cohesive model for the prevention of corruption.

The prevention model developed in this paper assists in deterring corruption, improving internal controls, improving the likelihood of detection and reducing opportunities to perpetrate corruption. By reducing the risk of corruption, this model also helps organizations and governments reduce project costs (public spending) and improve project quality, thus promoting economic competitiveness.

A comprehensive prevention model is developed to help curtail corruption and its devastating effects.