What does Objectivity Mean? Definition and Example

Two markers read the same essay. One awards 68, the other 58. Nothing about the essay changed in between.

Objectivity is one of the three main quality criteria in quantitative research and is settled long before any analysis begins. Objectivity means that a result does not depend on who administers the instrument, who scores the answers and who interprets the values. Objectivity is secured through rules fixed before data collection starts: written instructions, a coding frame for open answers and interpretation thresholds that apply to every user. By the end you can say which of the three parts your own study covers.

📌 The key points at a glance

• Objectivity means the result does not depend on the researcher.
• Administration, scoring and interpretation are secured separately.
• Standardisation is the strongest single lever for objectivity.
• No single coefficient exists for objectivity itself.
• UK assessment discusses the same idea as marking reliability.

Objectivity means the result does not depend on the person

Objectivity means that a test or questionnaire measures the characteristic it is meant to measure independently of the person administering it and the person scoring it, and that clear, user-independent rules exist for interpreting the results.

An older name for the same criterion is intersubjective comparability. The underlying test question stays the same: do several people working separately with the same instrument arrive at the same result? Where the answer is no, the study is partly measuring the person who runs it. The other two main criteria are reliability and validity.

A confusion sits inside the everyday word. Objectivity does not require researchers to hold no opinion about their topic. What it requires is that the opinion cannot shift the result, because the procedure leaves it no room. Someone who has a hunch and still uses a standardised questionnaire is working objectively. Someone entirely open-minded who sorts free-text answers by instinct is not.

Administration, scoring, interpretation: the three parts of objectivity

Objectivity splits into three parts that follow the order of a study. The division goes back to Gustav Lienert and Ulrich Raatz and is still taught in this form.

The split matters in practice. Each part can be met or missed on its own, and in a dissertation each one is argued separately. A survey can be faultless in administration and leave every judgement call open at the scoring stage.

Administration objectivity: what the instructions have to contain

Administration objectivity means the result does not depend on who runs the data collection. In practice, everything a respondent sees is written down beforehand. That covers the introductory text, the explanation of the answer scale, the order of the questions and the note on what happens to the data. Leave any of these to the situation and you create exactly the difference between two sessions that the criterion is meant to rule out.

Scoring objectivity: open questions need a coding frame

Scoring objectivity means two people derive the same values from the same answers. With closed questions the problem barely arises, because each option maps to a fixed numerical value. As soon as free-text fields appear in the questionnaire, a coding frame has to exist before the first answer is read: the categories, a definition for each and an example for each. Whether the frame holds up only shows once two people apply it independently.

Interpretation objectivity: why norms are missing and what helps instead

Interpretation objectivity means different specialists draw the same conclusion from the same number. That would require norms from a standardisation sample, and a self-built survey has none. What takes their place are your own thresholds, set before you look at the data and stated in the methodology chapter. A mean of 3.4 on a Likert scale is neither good nor bad on its own.

How to build objectivity into your own survey

Objectivity is not added afterwards, it is built in before the study starts. Each of the three parts has one measure that a student project can realistically carry out, and one warning sign that it is missing.

The second row carries the most weight, because that is where the judgement calls sit. A coding frame written before the first answer is read removes the most common line of attack in a viva. Anyone running a quantitative study without any free-text fields avoids the problem altogether and loses the reasoning behind the numbers.

Objectivity in UK practice: standardisation and marking reliability

Objectivity is a heading from German-language methodology textbooks, where it sits beside reliability and validity as the third main criterion. UK assessment literature covers the same ground under other names, worth knowing before you use the word in a dissertation.

Ofqual, the qualifications regulator for England, discusses the administration and scoring side under standardisation and marking reliability. Its review of standardisation methods and mark schemes concludes that the most consistent factor across the evidence is the need for clarity in the mark scheme and the avoidance of unnecessary complications. In other words: the rules, not the attitude of the marker.

Double marking and moderation are not the same thing

Universities use two distinct mechanisms, and confusing them in a methodology chapter is an easy mark to lose. Durham University describes double marking as two separate markers each forming a judgement and then agreeing a mark, while moderation means a moderator looking at a sample of the work in a run.

There is no coefficient for objectivity itself

No single number expresses objectivity, unlike reliability with its value between 0 and 1. What can be quantified is agreement: where two people score the same open answers with the same coding frame, the degree of agreement is expressed as a coefficient, usually Cohen’s kappa. A boundary runs through here that many guides blur. The coding frame secures objectivity, while the measured agreement is reported as inter-rater reliability and belongs to reliability.

Common mistakes with objectivity

Three mistakes come up again and again in dissertations, and none of them is statistical. All three happen in the text about the method rather than in the data.

The cause is the same every time: objectivity is claimed for something it was never designed to do. Once you know the three confusions, you can find them in your own methodology chapter within minutes.

Confusing objectivity with the neutrality of the researcher

Objectivity is a property of the procedure, not a state of mind. Sentences such as “the study was objective because I approached the topic without preconceptions” therefore prove nothing. Objectivity is evidenced through the rules that limited the room for judgement: the questionnaire, the coding frame and the thresholds set in advance. Holding a hunch is no flaw but the normal case in an empirical dissertation.

Asserting objectivity in the methodology chapter without evidencing it

A sentence such as “objectivity is given” appears in a great many dissertations and contributes nothing. Marked is not the claim but the description of the procedure. One paragraph is enough: what every respondent saw, by which rules answers became values, and who set those rules.

Reading high objectivity as a sign of a good result

An objective study can miss the topic entirely. Objectivity says only that the result does not hang on the people involved, and nothing about whether the questions capture the characteristic you mean. That is the job of validity. A standardised questionnaire with the wrong questions reliably produces the same wrong picture.

Conclusion

Objectivity asks for the least arithmetic of the three criteria and is decided earliest. Nothing about it improves after data collection, because the rules had to be in force beforehand. An hour spent on instructions and a coding frame writes that part of the methodology chapter for you.

Objectivity says the result does not hang on you. Whether you measured the right thing, it does not say.

Where to go next

• Want all three criteria side by side? Objectivity, reliability and validity compared
• Need the definition of the next term? What does reliability mean?
• Looking for the full set of criteria? Reliability and validity: quality criteria in research
• Want the whole process in view? Fundamentals of empirical research

Our reading tip: Ofqual: Standardisation methods, mark schemes, and their impact on marking reliability. The review sets out what actually makes marking consistent and is freely available. For the test theory behind the three parts, see Moosbrugger, Helfried and Kelava, Augustin (eds.) (2012): Testtheorie und Fragebogenkonstruktion, 2nd edition, Springer.

Want every respondent to see the same questionnaire in the same order?

With empirio.ai, an online survey tool from Germany, you set the instructions, the question order and the answer scales once and then share the survey by link. Administration objectivity is largely covered that way; scoring and interpretation remain your job.

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