Kenzo Nera

If anyone has tips on how to recruit reviewers (when you handle a paper on a topic you do not know), I'm very keen to read them!

Being an associate editor. =_=

"It's for science and the CV".

Ah, l'ACTS c'est l'échelle de Joe Uscinski (qui est politologue). Elle fait plutôt autorité en sciences politiques du coup. Elle est bien (elle semble moins skewed que le CMQ) mais si c'est en psychologie, privilégie un outil de psychologie je dirais. CMQ, CMS, Generic Conspiracy Beliefs Scale...

Mais de toute façon, toutes ces échelles corrèlent à fond les unes avec les autres(r > .70 typiquement) donc peu de chances que ça impacte substantiellement tes résultats.

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je connais pas l'ACTS non plus! CMQ est clairement plus utilisé, mais pb d'effet plafond (scores en moyenne élevés). Si c'est en Anglais, je te conseille la Conspiracy Mentality Scale de Imhoff et Bruder (journals.sagepub.com/doi/full/10....). Elle est conceptuellement et psychométriquement propre.

I'd be happy to! Feel free to write me an email (kenzo.nera@ulb.be) or maybe we can grab a drink this summer at the EASP meeting in Strasbourg :)

Thank you for sharing Jan!

It also shows that knowledge comes in many forms, and that discovering that you have been wrong for years is one of them. One unpleasant form of knowledge, but one that ultimately gives the sense of having become a better researcher. 11/11

But hey, now it’s out. While Collabra: Psychology is not (yet) representative of the publishing system, it is another demonstration that the belief that “it’s impossible to publish null results” is – at least to some extent – a self-fulfilling prophecy. 10/11

I’m not gonna lie, it was not an easy one to get published. I had to contest a rejection letter and revise much of the paper. Most of the revisions were to improve clarity: it’s surprising how, even when the overarching narrative makes sense, it remains difficult to narrate mixed results. 9/11

It’s the first time I mention the publishing process in a paper and I think it’s kind of cool – it is a way to acknowledge the value of peer review within one’s own work. 8/11

I turned my “Look at my cool effect” paper into a “we thought we had an effect, but actually no, but it is still interesting, trust me” one. Disclosing all the studies – the ones that initially worked, along with the failed replications – was the most transparent approach, so I did that. 7/11

This was not an easy piece to write. Academia still equates good science with significant results, even though we all know it’s bullshit. But at the same time, I thought that if there was one moment when I had to truly live up to my ideals of transparency and “good science,” it was now or never.6/11

only to discover that the effect was completely gone. Were the reviewers right? I ran a bunch of replications – five – that mostly buried the effect I was once so proud to have discovered. 5/11

These studies were submitted for publication and rejected on the grounds that there was a methodological confound (whose nature I won’t spoil). I was confident that my effect was real, so I ran a highly powered replication with a corrected methodology… 4/11

They were not more likely to endorse the conspiratorial attribution itself, but still, how cool: when someone blames your ingroup for its predicament, you connect more with people promoting conspiracy stuff! 3/11

During my PhD, I ran a series of studies showing that when exposed to an internal attribution for an ingroup’s disadvantaged situation, people reported increased sympathy with the author of a conspiratorial attribution for said situation. 2/11

This was not an easy one to write, but here it is!

🎈🤡 Freshly published in Collabra: Psychology: the life and death of one of the coolest findings in my PhD dissertation. 🎈🤡

With the usual – and wonderful – Karen M. Douglas, @paulbertin.bsky.social, and @olivierklein.bsky.social.

1/11

Preprint is available at: osf.io/preprints/ps...

The second finding is that while the plausibility judgements vs. conviction distinction makes sense conceptually and might help data interpretation, it is unlikely to fundamentally challenge past research – notably due to very strong statistical overlap between the constructs. 9/9

Researchers should acknowledge that “belief in conspiracy theories” is to be understood broadly: as convictions, but also as less settled beliefs. 8/9

As a result, the interpretation of findings should not be narrowly framed in terms of convictions - which can be implicitly the case when using the generic expression “believing in conspiracy theories is associated with XYZ”. 7/9

That said, agreement scales seem to largely conflate conviction and plausibility judgements (e.g., agreement, plausibility, and veracity assessments are very tightly correlated despite some statistical discrepancies, with plausibility judgements being less skewed and, on average, higher). 6/9

Luckily for our field, our results suggest that agreement scales primarily measure conviction. For instance, in Study 1, most (76.9%) participants who reported complete (dis)agreement with specific conspiracy theories considered that the available evidence definitively proved their position. 5/9

This nuance is crucial because it can alter data interpretation. For instance, it is not irrational to consider two mutually contradictory claims simultaneously plausible; it is irrational to consider them simultaneously true. 4/9

Does someone who “completely agrees” with a conspiracy theory firmly believes that it is true, or do they merely express an agnostic plausibility judgement? This question has been a splinter in my brain since the very beginning of my PhD, seven years ago. 3/9

The psychological study of conspiracy theories overwhelmingly relies on agreement scales to measure belief in conspiracy theories. Yet, what these scales exactly capture remains unclear. 2/9

👽👽👽 New paper accepted in the European Journal of Social Psychology! 👽👽👽

“Convictions or Plausibility Judgements? The Ambiguity of Self-Reported Agreement with Conspiracy Theories”

It’s my first collaboration with the brilliant and most stylish Robbie Sutton, so it’s a double thrill. 1/9

With the great Robbie Sutton (University of Kent), Yasemin Uluşahin (Université libre de Bruxelles, @yaseminulusahin.bsky.social), and Magali Beylat (Université libre de Bruxelles, @magalibeylat.bsky.social)

As for range generalisability, we argue for a case-by-case evaluation for the possibility that relationships might be non-linear across the full range of agreement scores.

It is a working paper so we are very eager for feedback!

9/10