Smorgasbord: Twitter v. Mastodon; Incentivizing Open Science; DEI v. Involution

Another “mixed bag” post from us — Is it time to leave Twitter? How can we incentivize journals and authors to take up open science practices? What is “involution” and is DEIA the solution?

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Smorgasbord: A Better Metaphor for Publishing, Twitter/Musk, Equitable Access, and Those Vexing OACA Experimental Controls

A new type of post from us today, offering a smorgasbord of opinions on topics including the ongoing Twitter/Elon Musk saga, just what “equitable access” to the literature means, the ongoing lack of experimental controls in one area of bibliometric analysis, and whether journals are more like a gate or a sewer.

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Briefly Noted: ZBW MediaTalk in Test Mode on Mastodon

by Claudia Sittner

Profiles of public institutions on commercial social networks have long been a source of unease for data protectionists throughout Germany. But until 2016, there was a lack of equivalent alternatives. Mastodon could be one such alternative. The decentralised network by software developer Eugen Roschko is Open Source with the source code being freely available on Github. The decentralised nature of Mastodon is what makes it so attractive and a good choice from an Open Science perspective.

What is Mastodon? Video by Mastodon on Youtube

Unlike platforms such as Facebook or Twitter, it is non-commercial, free of advertising and run by volunteers, who can also be organisations, on so-called instances. The instances are nodes, i.e. servers, creating a decentralised network: The Fediverse – a cross between “Federated” and “Universe”. The Fediverse is the generic concept for a network of federated systems, which implements a specific protocol (ActivityPub) – like Mastodon.

Data protection and Mastodon

The network is not financed by advertising revenue, which in practice almost always means the collection and use of personal data. So it can be operated in compliance with data protection laws. For data protectionists, however, the decentralisation is the big bonus. It is considered more data-protection compliant because not all data is collected at a central point. Of course, commercial providers can also host an instance, but that would only be one of many. Many Mastodon nodes also have their own data protection statements. However, there are no contracts for Data Processing Agreements. The choice of an instance is, therefore, ultimately a matter of trust.

The increased compatibility with data protection led, among other things, to some German authorities (German) and data protection officers, such as the data protection officer of Baden-Württemberg, Stefan Brink (German), setting up a profile there.

Creating an account on Mastodon: two steps

On Mastodon, users can create accounts in two steps. In the first step, they choose a suitable instance. These differ in terms of the community that has settled there, the usage guidelines, the number of users, the language and the tone. The latter is defined in the usage rules of the instance. Anyone who does not abide by them can be excluded by the admins. Since the individual instances have far fewer accounts than other social networks, expulsion on Mastodon can actually happen quite quickly. It is even possible to exclude entire instances from the Fediverse if, for example, there are no rules of use or the users do not adhere to them and serious cross-account violations occur too frequently.

Finding a suitable instance

There are currently around 3,800 Mastodon instances and 5.2 million users (July 2022). Filter systems or blog posts such as this one (German) can help you find the right instance. When we created the MediaTalk account on Mastodon in 2018 – back then in the tail of the Cambridge Analytica scandal – we chose the OpenBiblio instance. It is run by the Staatsbibliothek zu Berlin (state library). OpenBiblio is constantly growing and currently hosts almost 400 profiles. Around 29,000 contributions have been posted here so far. In the meantime, the instance has become well established for the German-language library scene. In the second step, you can create the user account. The account URL also includes the name of the instance, in our case:

ZBW-MediaTalk on Mastodon

As can be seen from this example, the name of the instance can already say something about its background, thematic focus and the interests of its community. But don’t worry, choosing an instance is not a life decision: if you don’t feel at home, it is possible to switch. Followers can be taken along, some other things too, but unfortunately not postings.

Posting on Mastodon

To stay with our example: Just because our account is hosted on the OpenBiblio instance does not mean that we can only follow others on that instance and only see their posts, because all instances are linked to the Fediverse. Communication is often compared to e-mail: Even if I have a Googlemail account, I can write mails to users of a Hotmail account and receive mails from them. The practical thing is that with a Mastodon account, you can also follow users with profiles on other Fediverse services like Pixelfed, which is about photos.

So we can follow all other accounts and vice versa. Nothing stands in the way of writing your own posts, which are called “toots” on Mastodon. A toot consists of a maximum of 500 characters. As usual, pictures, videos or similar attachments can be sent along. What is called a “retweet” on Twitter is a “boost” on Mastodon. Instead of hearts or likes, users award stars.

MediaTalk in test mode on Mastodon

After the fuss about Elon Musk’s tweet about buying Twitter, we decided to fill our profile on Mastodon with life. Since we are doing this in test mode for the time being, we are mirroring our tweets there. We currently use the command line tool t2m for this. It’s a bit on the old side, but it’s Open Source and can be easily operated on your own server. There are also online tools for this form of mirroring, but their use in compliance with data protection regulations is questionable. For the reasons mentioned, we are now active on Mastodon, for the time being. But we are confident that we will be there permanently. In what form, after a certain test phase, is still open. So if you are no longer happy on Twitter, maybe because of data protection concerns, you won’t miss anything if you follow us on Mastodon. We would be happy to welcome you there!

This text has been translated from German.

Read more about Mastodon:

Read more on MediaTalk:

About the author

Claudia Sittner studied journalism and languages in Hamburg and London. She was a long time lecturer at the ZBW publication Wirtschaftsdienst – a journal for economic policy, and is now the managing editor of the blog ZBW MediaTalk. She is also a freelance travel blogger (German), speaker and author. She can also be found on LinkedIn, Twitter and Xing.
Portrait: Claudia Sittner©

Featured Image: Mastodon press kit

The post Briefly Noted: ZBW MediaTalk in Test Mode on Mastodon first appeared on ZBW MediaTalk.

Desperately Seeking (Statistical) Significance

Twitter does not increase citations, a reanalysis of author data shows. Did the authors p-hack their data?

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Fill in the Blank Leads to More Citations

When a reputable journal refuses to get involved with a questionable paper, science looks less like a self-correcting enterprise and more like a way to amass media attention.

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Maximizing the rigor and reproducibility of citizen science in ecological research

PLOS ONE is organizing a Twitter chat on citizen science methodologies on 2nd April- see details below

Citizen science (CS) encompasses a broad range of research methodologies that involve public participation for data collection, transcription or analysis. Applications of CS have been found in many disciplines, but ecology has consistently been at the forefront. While some CS-based ecological monitoring schemes- such as the UK Butterfly Monitoring Scheme, established in 1976- have been running for decades, the popularity of CS has grown rapidly in more recent years. A wide range of projects based on CS methodologies are now being undertaken around the world, at local, national and international scales. The value of volunteer participation in activities ranging from transect-based species monitoring (Wepprich et al., 2019) and collection of biological specimens for lab-based analysis (Larson et al., 2020; Rasmussen et al., 2020) to crowdsourcing of creative thinking for study design (Can et al., 2017), has been repeatedly demonstrated.  Studies have also highlighted the particular utility of CS methodologies in supporting long-term ecological monitoring in resource-limited contexts, including in economically developing countries (Gouraguine et al., 2019). Meanwhile, examples of the real-world impact of CS research are abundant, both in specific ecological interventions and the wider political discourse. For instance, the influential UK State of Nature 2019 report, likely to be a key source of evidence for future environmental legislation, cites the outcomes of a wealth of CS projects.

With the expansion of CS research, there is lively debate about how to maximise rigor and reproducibility in different types of CS methodologies. One of the crucial aspects of a successful CS study is an appropriately designed protocol, which features a realistic degree of complexity and accounts for the specific challenges of handling CS-derived data. An example of this is provided by a recent comprehensive report of the design, launch and assessment of the UK National Plant Monitoring Scheme (Pescott et al., 2019). Pre-testing of protocols prior to project launch can provide confidence in the robustness of the study design. When designing a CS study, it is also important to understand volunteer motivation and ensure that this is appropriately matched with the nature of the task to be performed (Lyons & Zhang, 2019). Some CS studies utilize narrower demographic groups to meet the required level of motivation and understanding, such as amateur naturalists (Hallmann et al., 2017) or students who are following a course in a related topic (Chiovitti et al., 2019). Depending on the type of study, researchers may also plan to support CS volunteers with training or technological aids, increasingly in the form of mobile apps (Ožana et al., 2019; Appenfeller et al., 2020).



A certain amount of error, either random or systematic, is likely to be introduced by the collection of data by CS volunteers, and study designs must account for this. The level of error can be reduced by allowing volunteers to provide clarifying metadata or to register uncertainty (Torre et al., 2019), or using incentives to reduce sampling bias (Callaghan et al., 2019), but researchers should also ensure that they have means to assess the accuracy of contributed data (Falk et al., 2019; Gibson et al., 2019). Much ecological research is based on large public databases of volunteer-contributed records of species distributions, phenological events and other observational data (e.g. Siljamo et al., 2020). There is an active discussion in the ecological research community about how to maximize the reliability and utility of such data (Ball-Damerow et al., 2019).

The particular considerations that have to be made in the design, execution and evaluation of CS studies has led to calls for dedicated standards and guidelines for CS research. Of course, any such tools must strike the balance between promoting appropriate levels of standardization and allowing the flexibility required for applications of CS methodologies across diverse settings and research questions. Whilst some progress has been made towards this goal, maintaining an open and constructive dialogue among CS practitioners and other stakeholders remains critical to ensure that researchers, volunteers and society are able to realize the full potential of CS.

To foster discussion of these important issues, PLOS ONE (@plosone) will be moderating a Twitter chat on citizen science methodologies on Thursday 2nd April starting at 4pm BST (8am PDT, 11am EDT, 5pm CET). This is a chance for the CS community to share perspectives, experiences and suggestions for best practice. We’ll aim to cover the following questions (and more!):

  • How far can methods in CS projects be standardized?
  • What steps should be taken to maximize CS data quality?
  • Is there a need for clearer guidelines for the design and execution of CS studies?
  • How should credit for data collection be apportioned?

You can take part by using the hashtag #citscichat– we hope to see you there!



Appenfeller LR, Lloyd S, Szendrei Z (2020) Citizen science improves our understanding of the impact of soil management on wild pollinator abundance in agroecosystems. PLoS ONE 15(3): e0230007.

Ball-Damerow JE, Brenskelle L, Barve N, Soltis PS, Sierwald P, Bieler R, et al. (2019) Research applications of primary biodiversity databases in the digital age. PLoS ONE 14(9): e0215794.

Callaghan CT, Rowley JJL, Cornwell WK, Poore AGB, Major RE (2019) Improving big citizen science data: Moving beyond haphazard sampling. PLoS Biol 17(6): e3000357.

Can ÖE, D’Cruze N, Balaskas M, Macdonald DW (2017) Scientific crowdsourcing in wildlife research and conservation: Tigers (Panthera tigris) as a case study. PLoS Biol 15(3): e2001001.

Chiovitti A, Thorpe F, Gorman C, Cuxson JL, Robevska G, Szwed C, et al. (2019) A citizen science model for implementing statewide educational DNA barcoding. PLoS ONE 14(1): e0208604.

Falk S, Foster G, Comont R, Conroy J, Bostock H, Salisbury A, et al. (2019) Evaluating the ability of citizen scientists to identify bumblebee (Bombus) species. PLoS ONE 14(6): e0218614.

Gibson KJ, Streich MK, Topping TS, Stunz GW (2019) Utility of citizen science data: A case study in land-based shark fishing. PLoS ONE 14(12): e0226782.

Gouraguine A, Moranta J, Ruiz-Frau A, Hinz H, Reñones O, Ferse SCA, et al. (2019) Citizen science in data and resource-limited areas: A tool to detect long-term ecosystem changes. PLoS ONE 14(1): e0210007.

Hallmann CA, Sorg M, Jongejans E, Siepel H, Hofland N, Schwan H, et al. (2017) More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12(10): e0185809.

Larson RN, Brown JL, Karels T, Riley SPD (2020) Effects of urbanization on resource use and individual specialization in coyotes (Canis latrans) in southern California. PLoS ONE 15(2): e0228881.

Lyons E, Zhang L (2019) Trade-offs in motivating volunteer effort: Experimental evidence on voluntary contributions to science. PLoS ONE 14(11): e0224946.

Ožana S, Burda M, Hykel M, Malina M, Prášek M, Bárta D, et al. (2019) Dragonfly Hunter CZ: Mobile application for biological species recognition in citizen science. PLoS ONE 14(1): e0210370.

Pescott OL, Walker KJ, Harris F, New H, Cheffings CM, Newton N, et al. (2019) The design, launch and assessment of a new volunteer-based plant monitoring scheme for the United Kingdom. PLoS ONE 14(4): e0215891.

Rasmussen SL, Nielsen JL, Jones OR, Berg TB, Pertoldi C (2020) Genetic structure of the European hedgehog (Erinaceus europaeus) in Denmark. PLoS ONE 15(1): e0227205.

Siljamo P, Ashbrook K, Comont RF, Skjøth CA (2020) Do atmospheric events explain the arrival of an invasive ladybird (Harmonia axyridis) in the UK? PLoS ONE 15(1): e0219335.

Torre M, Nakayama S, Tolbert TJ, Porfiri M (2019) Producing knowledge by admitting ignorance: Enhancing data quality through an “I don’t know” option in citizen science. PLoS ONE 14(2): e0211907.

Wepprich T, Adrion JR, Ries L, Wiedmann J, Haddad NM (2019) Butterfly abundance declines over 20 years of systematic monitoring in Ohio, USA. PLoS ONE 14(7): e0216270.


All images used under Pixabay licence.

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“Low T” and Prescription Testosterone: Public Viewing of the Science Does Matter


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