I feel ashamed that my name is on it. I wish I could retract it.
So, yes please: make it hard to impossible for paper mills and kill the whole publish or perish approach.
I contributed nothing other than a statistical framework which was discarded when it broke their predefined conclusion.
I think as children if we are taught what earning a living means, people who only want to make ends meet would try to do it using other less damaging methods. For e.g., sales and marketing are not bad places for such people. When it comes to research people should know that perhaps money will not be great.
It is because we aren't aware of the full picture as children, we follow our passions (or we follow cool passions) and then realise that money is also important and then resort to unethical means to get that money. Let's be transparent about hard fields with children so that when they enter such fields they know what they are getting into.
I think in some fields you walk into them with some kind of noble ideology, possibly driven by marketing but then you find out it's all bullshit and you're n-years into your educational investment then. Your options are to shrug and join in or write everything off and walk away.
I don't blame people for taking advantage of it but in some areas, particularly health related, there are consequences to society past financial concerns.
A few computer science friends of mine worked at a social science department during university. Their tasks included maintaining the computers, but also support the researchers with experiment design (if computers were involved) and statistical analysis. They got into trouble because they didn't want to use unsound or incorrect methods.
The general train of thought was not "does the data confirm my hypothesis?" but "how can I make my data confirm my hypothesis?" instead. Often experiments were biased to achieve the desired results.
As a result, these scientific misconduct was business as usual and the guys eventually quit.
At least in the social sciences there is an expectation of having some data!
There's huge amounts of data available (geography, lots and lots of maps; history, huge amount of historical documentation; economics, vast amounts of public datasets produced every month by most governments; political science, censuses, voting records, driver registrations, political contest results all over the Earth - often for decades if not centuries).
Most is relatively well verified, and often tells you how it was verified [2]. Often it's obtainable in publicly available datasets that numerous other researchers can verify was obtained from a legitimate source. [3][4][5][6][7][8][9][10][11][12]
There's lots of data available. Much is also verifiable in a very personal way simply by walking somewhere and looking. In many ways, social sciences should be one of the most rigorous disciplines in most of academia.
[1] Using Wikipedia's grouping on "social sciences" (anthropology, archaeology, economics, geography, history, linguistics, management, communication studies, psychology, culturology and political science): https://en.wikipedia.org/wiki/Social_science
[2] Census 2020, Data Quality: https://www.census.gov/programs-surveys/decennial-census/dec...
[3] Economic Indicators by Country: https://tradingeconomics.com/indicators
[4] Our World in Data (with Demographics, Health, Poverty, Education, Innovation, Community Wellbeing, Democracy): https://ourworldindata.org/
[5] Observatory of Economic Complexity: https://oec.world/en
[6] iNaturalist (at least from a biological history perspective): https://www.inaturalist.org/taxa/43577-Pan-troglodytes
[7] Coalition for Archaeological Synthesis, Data Sources: https://www.archsynth.org/resources/data-sources/
[8] Language Goldmine (linguistics datasets): http://languagegoldmine.com/
[9] Pew Research (regular surveys on economics, political science, religion, communication, psychology - usually 10,000 respondents United States, 1000 respondents international): https://www.pewresearch.org/
[10] Marinetraffic (worldwide cargo shipping): https://www.marinetraffic.com/en/ais/home/centerx:-12.0/cent...
[11] Flightradar Aviation Data (people movement): https://www.flightradar24.com/data
[12] Windy Worldwide Web Cameras: https://www.windy.com/?42.892,-104.326,5,p:cams
I’ll reduce it to a part of psychology.
Research fraud is common pretty much everywhere in academia, especially where there's money, i.e. adjacent to industry.
Observations: Firstly inventing a conclusion is a big problem. I'm not even talking about a hypothesis that needs to be tested but a conclusion. A vague ambiguous hypothesis which was likely true was invented to support the conclusion and the relationship inverted. Then data was selected and fitted until there was a level of confidence where it was worth publishing it. Secondly they were using very subjective data collection methods by extremely biased people then mangling and interpolating it to make it look like there was more observation data than there was. Thirdly when you do some honest research and not publish because it looks bad saying that the entire field is compromised for the conference coming up which everyone is really looking forward to and has booked flights and hotels already.
If you want to read some of the hellish bullshit, look up critique of the Q methodology.