This greatly reduces the incentive to replicate published studies - if you can't get funding to do something and you wouldn't be able to publish it anyway, it won't get done. Two other major and common obstacles to independent validation are:.
The lack of reproducibility of experiments is a problem in most areas of science and awareness of this is growing.
In this prompted the Reproducibility Initiative , where researchers can pay a fee for blind, independent replication prior to publication. This sounded like a step in the right direction at the time but as far as I know awareness of the initiative remains fairly low, uptake has not been great and 'proper' reproduction remains very rare indeed. I'm not sure anyone is supposed to repeat experiments, in any formalized way.
In engineering, and I suppose physics, you end up repeating experiments because you are looking to use a method to solve a problem. So if someone has published a method to solve a particular problem, researchers will often try it in order to see how well it works for their system.
Some methods work better than others, and I guess the best performing methods will be cited and used and become well known.
Methods that don't work, or method with flaws and errors will tend to be forgotten over time. While it would be nice to repeat experiments, in practice we as a society don't really want 1 scientists to repeat them just because, we want them to create new knowledge instead.
However, for experiments that are both hard to perform and seem trustworthy, there is no incentive to repeat them, it would not be particularly useful for the required effort. If you're really sure about the results that you'll get, then you don't gain any information by doing it, and that's not research anymore. Researchers don't start their work from scratch.
New methods and objects appear to improve and extend previous research. As far as computer science is concerned, there are some journals that require experiments to be perfectly repeatable.
In such cases they even require randomizer seeds to be explicitly stated during the review stage. However, not all journals have this sort of constraint, it differs from one reviewer to another. Coming back to PhDs, in the end, it is nearly always up to the scholar to repeat the results to verify and refine them as needed.
If you are working in a research team, you could use the published results produced or repeated by your peers. The detector systems in the large collider experiments are enormously flexible devices, and each new generation can and does reproduce and refine the work of the previous generation of machines as part of it's commissions and general data analysis.
Something similar goes on with neutrino research, and low energy facilities also do a lot of that. My advisor was a nuclear physicist by original training who moved up the energy scale as time went by, and he once joked that nuclear physicists "do what particle physicist did twenty years ago, but ten to one hundred times as precisely" which is too broad a claim in general, but has enough truth in the non-perturbative regime to make it good snark. In my field sub-engineering , doing an experiment can be very costly and time consuming to be honest, I haven't really heard of anyone repeating a full experiment!
So, it is very common for a PhD student to test full scale specimens. For each experiment we do, we often develop a very detailed 3D, nonlinear, etc. This model is also used to conduct a parametric study. So, in a way and indirectly , the experiment is repeated! I worked for some years in discrete optimization and must say that most computational experiments are not repeated in any rigorous way.
From the scientific papers, it is usually not possible to reconstruct the method in detail because source code is not published. Post a comment or leave a trackback: Trackback URL. Posted October 5, at am Permalink. Posted October 30, at am Permalink. Posted February 4, at am Permalink. Posted February 8, at pm Permalink. Post a Comment Click here to cancel reply.
You must be logged in to post a comment. Create a free website or blog at WordPress. For some authors, replicability and reproducibility can be used interchangeably.
For others, the distinction is of great importance. Sometimes, authors have tried to swap them around or erase one altogether.
The history of these different attempts can be read in this excellent article. This can all be a bit confusing, but this guide, at least, will try to be clear, using previously established definitions of both terms: Reproducibility Different team, same experimental setup.
If an observation is reproducible, it should be able to be made by a different team repeating the experiment using the same experimental data and methods, under the same operating conditions, in the same or a different location, on multiple trials Replicability : Different team, different experimental setup. If an observation is replicable it should be able to be made by a different team, using a different measuring system and dataset, in a different location, on multiple trials.
This would therefore involve collecting data anew. Create a personalised content profile. Measure ad performance. Select basic ads. Create a personalised ads profile. Select personalised ads. Apply market research to generate audience insights.
Measure content performance. Develop and improve products. List of Partners vendors. Replication is a term referring to the repetition of a research study, generally with different situations and different subjects, to determine if the basic findings of the original study can be applied to other participants and circumstances.
Once a study has been conducted, researchers might be interested in determining if the results hold true in other settings or for other populations.
In other cases, scientists may want to replicate the experiment to further demonstrate the results. For example, imagine that health psychologists perform an experiment showing that hypnosis can be effective in helping middle-aged smokers kick their nicotine habit.
Other researchers might want to replicate the same study with younger smokers to see if they reach the same result. When studies are replicated and achieve the same or similar results as the original study, it gives greater validity to the findings.
When conducting a study or experiment , it is essential to have clearly defined operational definitions.
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