Data fudging is the deliberate manipulation or misrepresentation of data to produce desired outcomes, often by altering figures, cherry-picking favorable results, or adjusting methodologies. This unethical practice is typically employed by researchers seeking publishable findings, marketers inflating performance metrics, or executives meeting unrealistic targets. While short-term beneficiaries may gain funding, credibility, or bonuses, the practice ultimately undermines scientific integrity, erodes public trust, and distorts decision-making processes.
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