Are P-hacking and hypothesising after results are known considered misconduct in academia?

The Declaration of Helsinki was updated in 2013 to "mandate" that research involving human subjects must be pre-registered. While not perfect, pre-registration prevents many of these statistical manipulations. The idea of pre-registration is that publicly stating your hypotheses and the details of how they will be tested in advance reduces questionable statistical practices. For example, changing the number of subjects, the inclusion/exclusion criteria, or the statistical model are not allowed.

From my understanding, failure to comply with the Declaration of Helsinki would be considered unethical in Medicine, while in other fields the pre-registration aspect is being actively ignored. For example, articles are now being published with disclaimers like "this research was conducted in accordance with the 2013 Declaration of Helsinki except the study was not pre-registered".

In the US, for research funded by the NIH, "Research Misconduct" is a finding made by the NIH Office of Research Integrity. Other federal agencies have offices with similar responsibilities for research misconduct.

The ORI web site has a "RCR Casebook" of fictionalized example cases used in training researchers about responsible conduct of research and research misconduct. It also has case summaries for every case where misconduct was determined and administrative penalties are currently in force (that is, cases where someone has been barred from getting NIH funding for some period of time.) In my reading through the training materials and case summaries, I haven't seen any cases where p-hacking was found to constitute misconduct. The cases are much more about outright fabrication of data or suppression of inconvenient data (e.g. by throwing out "outliers") to achieve a desired result. It appears that from the ORI point of view p-hacking is not (yet) considered research misconduct.

More on what it takes to reach the level of "misconduct." The NIH recognizes three kinds of research misconduct:

Fabrication: Making up data or results and recording or reporting them.

Falsification: Manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record.

Plagiarism: The appropriation of another person's ideas, processes, results, or words without giving appropriate credit.

p-hacking wouldn't fit under "fabrication" or "plagiarism." It might count as "changing or omitting results such that the research is not accurately represented in the research record." However, the ORI also requires that:

There be a significant departure from accepted practices of the relevant research community; The misconduct be committed intentionally, knowingly, or recklessly; and The allegation be proven by a preponderance of the evidence.

That's a pretty high standard. I think it would be hard to make the case that p-hacking is a significant departure from accepted practice and furthermore a researcher could claim that they didn't intentionally do the p-hacking.

These types of data-straining behaviors are most certainly scientific sins, in the sense of being stains on one's conscience and reputation. My favorite discussion of such sins is the "Nine Circles of Scientific Hell."

Building a formal misconduct case around such data-straining would likely be very difficult, however, since they may quite easily and naturally arise from human propensities to fool ourselves. Many people who engage in de facto p-hacking are not aware of it, particularly when there are large volumes of data and powerful analytic tools in play. A beautiful illustration of both the problem and an appropriate scientific response is the wonderful study that used popular fMRI methods to localize cognitive functions in the brain of a dead salmon.