Related Experiment Video
Updated: Feb 18, 2026
08:12
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
3.0K
Scholarly Merits: From Measurement to Judgment.
1Psychologisches Institut, Universität Heidelberg.
Summary
Quantitative measurements may bias scholarly merit assessments. This study advocates for incorporating qualitative arguments into selection procedures for a more balanced evaluation of scholarly merit.
Area of Science:
- Psychological Science
- Scholarly Communication
Background:
- The journal "Perspectives on Psychological Science" recently discussed criteria for scholarly merit.
- A potential bias favoring quantitative measurements over informed qualitative judgments was identified.
Purpose of the Study:
- To critique the potential bias in scholarly merit evaluation.
- To advocate for a more inclusive selection procedure.
Main Methods:
- Analysis of the discussion on scholarly merit criteria.
- Argumentation for the inclusion of qualitative assessment methods.
Main Results:
- Identified a potential bias towards quantitative metrics in evaluating scholarly merit.
- Highlighted the limitations of purely quantitative assessments.
Conclusions:
- Scholarly merit evaluation may be skewed by an overreliance on quantitative data.
- A balanced approach incorporating qualitative arguments is necessary for a comprehensive assessment of scholarly merit.
More Related Videos
10:39Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
Published on: August 29, 2025
1.2K
16:23Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Published on: February 26, 2014
15.0K
Related Concept Videos
01:52Accuracy and Precision
15.9K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate...
15.9K
01:11Statistical Analysis: Overview
16.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
16.7K
03:37Uncertainty in Measurement: Accuracy and Precision
108.7K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
108.7K
01:29Measures of Intelligence
8.6K
Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
8.6K
02:46Uncertainty in Measurement: Reading Instruments
54.3K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
54.3K
00:55Ordinal Level of Measurement
34.8K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
34.8K