Avoiding Confirmation Bias through Awareness and Training
2010
- 512Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage512
- Abstract Views300
- Downloads212
Thesis / Dissertation Description
In any profession where conclusions or opinions are generated by humans, there is a realization of possible error. In the profession of forensic science, errors are not taken lightly. In fact most agencies have been known to have had a no tolerance policy when it comes to errors. This means that if an analyst made a mistake in casework, he or she could be terminated. Over the past 15 years, the words "error" and "bias" have become synonymous with forensic science in the media. Major errors have surfaced in several high profile cases only to cast doubt on the forensic science system as a whole. There is speculation that the underlying cause of all these errors is bias. The recent National Academy of the Sciences (NAS) report has identified bias as an issue that needs to be dealt with. There have also been several studies on bias in forensic science that have provided empirical evidence of its existence. However, there have not been any studies to test whether or not bias can be avoided through awareness or training.
Bibliographic Details
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