Describing something that is not based on or influenced by personal feelings, tastes, or opinions; existing independently of the mind. It refers to observations, judgments, or assessments that are factual, impartial, and verifiable by objective criteria. This often applies to assessments that can be made with consistent, universal standards, unlike those interpretations that depend on the individual's perspective, preferences or emotional response. The concept is often relevant in fields like science, law, and statistics where unbiased observation is paramount for reliability and accuracy. Its use often helps remove personal bias and promote fairness.
Non-subjective meaning with examples
- A scientific experiment is designed to produce non-subjective results. By meticulously controlling variables and using standardized procedures, scientists aim to produce data that can be replicated by anyone, regardless of their personal beliefs, in order to test a hypothesis. This objective approach contributes to reliable and verifiable discoveries. This distinguishes scientific inquiry from personal experience, making it universally applicable.
- When evaluating a candidate, a hiring manager should use non-subjective criteria. Instead of relying on gut feelings or personal biases, decisions are made based on the candidate’s qualifications, experience, and the assessment of how their skills align with the job requirements. This objective process ensures fairness and equal opportunities for all applicants. It is crucial to avoid personal prejudice.
- A court of law aims to render non-subjective judgments. Evidence and testimony presented by a defendant are evaluated against established legal principles. Judgments and sentencing should be based on the laws in place, not on the judge's feelings towards the defendant or the crime, to guarantee fairness and impartiality. This process of impartiality is crucial to upholding justice.
- In data analysis, analysts strive for non-subjective interpretations. Instead of imposing personal biases onto the information, they interpret statistics using clear, standardized methods, and verifiable data. This objective approach helps reveal real patterns and trends in information. This ensures the integrity of the findings and their validity to a wide range of readers.