with all good intentions, the result is not very useful: "Predatory journals and publishers are entities that prioritize self-interest at the expense of scholarship and .. 1/

... are characterized by false or misleading information, deviation from best editorial and publication practices, a lack of transparency, and/or the use of aggressive and indiscriminate solicitation practices.” 2/
one of mistakes I think the consensus model made is that it has too much circular bootstrapping. Something is predatory because what we do not find predatory is not. E.g. the point about transparency. Just check how "transparent" some major publishers are in @RetractionWatch. 3/
@RetractionWatch the "best editorial and publication practices" turns out to focus on same basic agreements, mostly among publishers, and not really about doing quality science. It's an administrative rule. 4/
@RetractionWatch "Aggressive, indiscriminate solicitation" is also a rule really hard to apply. Elsevier repeatedly breaks this rule, and other more traditional publishers do too, tho at a lower frequency. Do the authors want to claim Elsevier is a predatory publisher? 5/
@RetractionWatch defining criteria of what a predatory publisher is, is hard. Some of the "lists" before them have tried (and failed). Will this list do better? I do not know. But either you make crystal clear objective rules instead of subjective, or go subjective all the way. 6/
@RetractionWatch the latter is not too hard to implement: just ask many authors multiple times to rank two journals. Like ranked voting. Caveat: you'll find may orthogonal reasons why the ranking was made ("I know the editor", "it's my society's journal", etc). 7/
@RetractionWatch but hey, any attempt to collapse this complex behavior into a single "predatory journal" list suffers from this too. https://t.co/r4XOLc7WZQ 8/8
@threadreaderapp unroll

More from Education

New from me:

I’m launching my Forecasting For SEO course next month.

It’s everything I’ve learned, tried and tested about SEO forecasting.

The course: https://t.co/bovuIns9OZ

Following along 👇

Why forecasting?

Last year I launched
https://t.co/I6osuvrGAK to provide reliable forecasts to SEO teams.

It went crazy.

I also noticed an appetite for learning more about forecasting and reached out on Twitter to gauge interest:

The interest encouraged me to make a start...

I’ve also been inspired by what others are doing: @tom_hirst, @dvassallo and @azarchick 👏👏

And their guts to be build so openly in public.

So here goes it...

In the last 2 years I’ve only written 3 blog posts on my site.

- Probabilistic thinking in SEO
- Rethinking technical SEO audits
- How to deliver better SEO strategies.

I only write when I feel like I’ve got something to say.

With forecasting, I’ve got something to say. 💭

There are mixed feelings about forecasting in the SEO industry.

Uncertainty is everywhere. Algorithm updates impacting rankings, economic challenges impacting demand.

It’s difficult. 😩
Department List of UCAS-China PROFESSORs for ANSO, CSC and UCAS (fully or partial) Scholarship Acceptance
1) UCAS School of physical sciences Professor
https://t.co/9X8OheIvRw
2) UCAS School of mathematical sciences Professor

3) UCAS School of nuclear sciences and technology
https://t.co/nQH8JnewcJ
4) UCAS School of astronomy and space sciences
https://t.co/7Ikc6CuKHZ
5) UCAS School of engineering

6) Geotechnical Engineering Teaching and Research Office
https://t.co/jBCJW7UKlQ
7) Multi-scale Mechanics Teaching and Research Section
https://t.co/eqfQnX1LEQ
😎 Microgravity Science Teaching and Research

9) High temperature gas dynamics teaching and research section
https://t.co/tVIdKgTPl3
10) Department of Biomechanics and Medical Engineering
https://t.co/ubW4xhZY2R
11) Ocean Engineering Teaching and Research

12) Department of Dynamics and Advanced Manufacturing
https://t.co/42BKXEugGv
13) Refrigeration and Cryogenic Engineering Teaching and Research Office
https://t.co/pZdUXFTvw3
14) Power Machinery and Engineering Teaching and Research
Time for some thoughts on schools given the revised SickKids document and the fact that ON decided to leave most schools closed. ON is not the only jurisdiction to do so, but important to note that many jurisdictions would not have done so -even with higher incidence rates.


As outlined in the tweet by @NishaOttawa yesterday, the situation is complex, and not a simple right or wrong https://t.co/DO0v3j9wzr. And no one needs to list all the potential risks and downsides of prolonged school closures.


On the other hand: while school closures do not directly protect our most vulnerable in long-term care at all, one cannot deny that any factor potentially increasing community transmission may have an indirect effect on the risk to these institutions, and on healthcare.

The question is: to what extend do schools contribute to transmission, and how to balance this against the risk of prolonged school closures. The leaked data from yesterday shows a mixed picture -schools are neither unicorns (ie COVID free) nor infernos.

Assuming this data is largely correct -while waiting for an official publication of the data, it shows first and foremost the known high case numbers at Thorncliff, while other schools had been doing very well -are safe- reiterating the impact of socioeconomics on the COVID risk.
This seems like a positive base from which to #BuildBackBetter


https://t.co/OwpgNh8mEu


https://t.co/7eOi1Bv3bM


https://t.co/GhxVgLuWJE


https://t.co/ymHp910wrC

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