Joshua Conrad Jackson

I am happy to announce that our project on risk and social learning is now in press at Psychological Review. Several new additions and revisions thanks to detailed feedback from colleagues and anonymous reviewers. osf.io/preprints/so...
@psmaldino.bsky.social @babeheim.bsky.social

Check out the whole paper for many more findings, robustness checks, and to see the work of a rising 💫 @hongkai1.bsky.social

Coolest evidence for differentiation as a cause might be an experiment (n=4000) simulating a comment thread

Incentivizing comment uniqueness (but not conformity) leads negative discourse to rise over time

Coauthored w @williambrady.bsky.social, @ycleong.bsky.social, Yutong Jiang, and Alex Koch

🚨New preprint🚨

osf.io/preprints/ps...

In a sample of ~2 billion comments, social media discourse becomes more negative over time

Archival and experimental findings suggest this is a byproduct of people trying to differentiate themselves

Led by @hongkai1.bsky.social in his 1st year (!) of his PhD

The @spspnews.bsky.social Religion & Spirituality Preconference is accepting applications for talks, data blitzes, & posters until 10/23! We're excited to hear from Kathleen Corriveau, @alexandraworm.bsky.social, @drmeltemyucel.bsky.social & @joshcjackson.bsky.social. More info: tinyurl.com/33x9za7r

One of my favorite conferences, @culturalevolsoc.bsky.social, just released key dates and other info!

I highly recommend checking it out for great research from across the social, behavioral, and natural sciences

Complex technology requires cultural innovations for distributing cognition Over the last decade, new research has shown how human collectives can develop technologies that no single individual could discover on their own. How…

🚨 New paper alert! (slightly belated)

We (with @joshcjackson.bsky.social) suggest that complex technologies, as they need several (often many) people to use them, require innovations that distribute cognition to help regulate cognitive load and coordinate.

www.sciencedirect.com/science/arti...

How religion declines around the world A country’s religious affiliation tends to decline in three transitional stages that unfold across generations, a new paper using Center data proposes.

Below is my new post about our Three Stages of Religious Decline paper (www.nature.com/articles/s41...).

We argue that a similar process of decline affects countries on every populated continent, including countries in which Christianity, Islam, Buddhism or Hinduism is the largest religion.

A🧵

@helenamiton.bsky.social and I have a new paper out:

www.sciencedirect.com/science/arti...

Past theories focus on how we evolve complex technologies (jet engines), but neglect cultural innovations that help us operate these technologies (pilot checklist)

Paper has tons of examples and new theory!

Social media often feels saturated with politics and morality - but is that feeling accurate? Our new paper finds that moralization has increased markedly on social media from 2013-2021, more than traditional media. See 🧵 below!

One of the largest-scale analyses of historical text data that I have contributed to

The finding: language on social media has become more moralized over the 21st century; we don't see the same trends on news media

Kudos to the first author @curtispuryear.bsky.social on the enormous effort

Alex Koch contributed endless theoretical insights over two years

Tessa Charlesworth gave some of the most useful and thorough comments I have ever read

And @andyluttrell.bsky.social pushed this paper to the point it is now

I also want to recognize the authors once more:

@yuanzeliu.bsky.social completed this massive project as a pre-doc, which speaks to his promise as a scholar

Our general discussion covers this framework in great depth, and uses it to make tentative inferences about all of our findings

This is a working paper, so any feedback would be helpful!

- When social dilemmas change, trait language changes -

Example: The rising division of labor over the last 200 years has meant that people are selected on specific competences

This might be one reason why agency language has become more semantically heterogeneous

- We use trait words as diagnostic tools for prediction -

Example: We may have many negative communal words because cooperation is common, so it is more diagnostic to communicate about deviations from cooperation

But since skill is rare in most domains, we have many positive words about agency

- Trait words reflect the nature of social dilemmas -

Example: We view three of the FACT dimensions as mapping onto classic social dilemmas identified in game theory

-Communion ➡️ cooperation
-Traditionalism ➡️ coordination
-Agency ➡️ whether people can cooperate and coordinate

Our approach makes several simple assumptions that encompass our different findings

1. Trait words reflect the nature of social dilemmas

2. We use trait words as diagnostic tools for prediction in these dilemmas

3. When social dilemmas change, we also change our trait language

The general discussion of our paper reviews these findings using a new “functional constructionist” approach to trait words, building on past work in emotion

Functional ➡️ trait words are useful
Constructionist ➡️ There is no single trait space

We find that communion words are converging in semantic space—extending work on the collapse of morality into a single dimension (cdr.lib.unc.edu/downloads/g7...)

But words about agency/competence are diverging in semantic space. They are becoming less related to each other over time

We also see interesting trends in the semantic coherence of these factors

We calculate coherence by looking at clustering in semantic space over time from word embeddings

Here are clusters of words projected based on their 19th and 20th century embeddings

The small change we do see is a surge of “traditionalism” words around the rise of participatory democracies in Europe

“Conservativism-liberalism” is the “youngest” trait dimension by date of introduction

Finally, we look at the history of trait words using dates of origin from the Oxford English Dictionary

This plot shocked me – our trait vocabulary has been remarkably stable over time

We have always had more words about communion and the fewest words about fitness

Negative and positive words are also vary in their specificity.

Negative are more likely to be specific, whereas positive words are more likely to generalize across many dimensions

Are there more negative or positive trait words? I once assumed there were more negative words because of negativity dominance

The real story is complicated

Communion dimensions are indeed filled with negative words.

But we have more positive words about agency, traditionalism, and fitness

Most trait dimensions are evaluative – the have positively and negatively valenced poles (it is good to be friendly and bad to be unfriendly)

But some dimensions are not. Communion and agency are more evaluative than traditionalism or fitness dimensions

For example, we find that Communion words are highly clustered (eg. words expressing friendliness tend to also express morality)

But words about traditionalism are spread across the network, closely knit with communion and agency

Although this FACT model is interesting and parsimonious, it masks variation within factors, and links between factors

The network below shows all words connected by their overlapping semantics.

The FACT factors partly organize the network, but lots of complexity remains

In an EFA, these 24 dimensions reduced to a four-dimension FACT model

Fitness (e.g., Attractiveness)
Agency (e.g., Assertiveness)
Communion (e.g., Morality)
Traditionalism (e.g., Conservatism)

Our model contains parts of prior models, most notably the ABC model of social evaluation

After collecting the words, we turned to their semantic structure

We took 24 dimensions from a review of personality and psych science lit. Then Prolific workers rated all words on these dimensions

This plot shows how some words are generalized (relevant to many dimensions); others are specific