There is something rotten in the Research Council of Norway

In the last couple of years, there has been a debate, especially in Khrono, concerning how the Research Council of Norway evaluates and funds scientific proposals.

There have been several stories whereby submissions to the Research Council of Norway (RCN) have been unfavourably assessed but then secured funding from the European Research Council (ERC).

ERC funds basic science, same as the RCN’s FRIPRO, or “Ground-breaking research”,  programme.

For example, this story shows that two rejections from the Research Council of Norway resulted in a Starting Grant from ERC.

Or this story, where the RCN assigned very low grades on a proposal but the outcome in ERC was securing an ERC Consolidator grant.

This story is illuminating because the proposal submitted to RCN was just a shortened version of the one submitted to ERC. In effect, the main underlying idea and approach were the same.

Nevertheless, the average grade in the Research Council of Norway was 4 and represented the lowest grade the PI had ever received before!

In contrast, to receive funding from ERC, you need grade A (fully meets the ERC’s excellence criterion and is recommended for funding if sufficient funds are available) during two evaluation steps.

Similar stories abound, and the Research Council of Norway’s explanation is that evaluations are by nature subjective.

This is, of course, true but begs the question of whether there are some fundamental flaws in the evaluation process in the Research Council of Norway.

For example, I now find myself in the same situation: I’ve submitted more or less the same proposal 3 different times to the RCN and have received the average grade of 4 with no funding (see a news story here).

Last year I submitted an expanded version to ERC and was notified on the 9th of March that the project was approved for funding (ERC Consolidator Grant, see here for details about the project).

While the evaluations are subjective, especially concerning scientific excellence, some criteria are less so.

For example, PIs and scientific group evaluations are somewhat objective as they are based on track records documented by publications, previous grants, etc.

Compare, for example, assessments I’ve received in 2012 vis-vis assessments I’ve received in the last 3 submissions:

In 2012 I submitted a proposal where ‘The project manager and project group’ assessment got a 6 – Excellent. The meaning of this grade is:

“The project leader and/or research/project group is qualified at a high international level, has contacts within the foremost national and international research environments and will be able to play an important role in ensuring the success of the project.”

10 years on, with more leadership experience, loads more publications ++ and the evaluation has fallen to 4 – Good on all 3 submissions!

Granted, there are differences in how these grades are assigned: PI and group are now evaluated under ‘Implementation’, which also includes ‘feasibility’. Previously, ‘feasibility’ was a separate category (by the way, I received a 6 on this in 2012 also!).

But this only goes to show that the evaluation criteria used by the RCN have changed.

A change that apparently opens for more vague and less concrete evaluations: the fact is that before 2019 all the proposals I submitted scored on overall 6 (or, in one case, 7 whereby I got a Young Research Talent grant), but after 2018 I’ve scored on overall 4.

Compare this with the assessment from ERC, where 7 different reviewers scored my capabilities as a PI as ‘Exceptional’, ‘Excellent’ or ‘Very Good’.

If one subscribes to an idea that the evaluation process in ERC is better suited to pinpoint ground-breaking research—whatever that might be—the inescapable conclusion is that the RCN has designed an evaluation system that is missing the most innovative (a buzzword that RCN is mightily fond off) projects, at least in terms scientific excellence.

In fact, looking at the level of written evaluations from the RCN, it would be better to randomly select people in the Norwegian population and ask them what they think.

That would at least provide an unbiased evaluation process.


Can political complexity evolve from small-scale cooperative herding groups?

Last week I was informed that my project proposal “From small-scale cooperative herding groups to nomadic empires – a cross-cultural approach (COMPLEXITY)” was funded through the ERC Consolidator Grant scheme.

Had to wait to announce it since it was not official until 12:00 17.03.2022 when ERC announces their press release with all the successful grants. The press release can be found here.

The overall aim of the Consolidator Grant is to “… support mid-career researchers and will help them consolidate their teams and conduct pioneering research on topics and with methods of their choosing” (from press release).

Central thesis

COMPLEXITY is situated at the intersection of anthropology and ecology and deals with the evolution of political complexity.

The prevalent view of the evolution of complex societies favours agriculture as the main factor.

How do we then explain the rise of nomadic empires?

One common explanation refers to conflict, and large-scale conflict with China has been presented as the central element in the rise of, for example, the Mongol Empire.

In 1242, Europe stood on the precipice of destruction. Based in Hungary and Serbia, the Mongol armies were poised for conquering the rest of Europe. Only the death of the Great Khan halted the Mongol advance, sparing Europe from the fate of an inevitable conquest. Twenty-five years after the withdrawal, the Mongol Empire reached its peak with the establishment of the Yuan dynasty – making it the largest land empire in history, stretching from the Sea of Japan to the Mediterranean Sea and the Carpathian Mountains.

Thus, pastoralists could only develop complex levels of organisation when facing strong agricultural neighbours.

But this cannot explain how pastoralists transitioned from small, kin-based groups to complex stratified societies.

COMPLEXITY’s central thesis is that before large-scale conflict is even possible, a level of within-group cooperation must be present.

Noteworthy, it is almost impossible for pastoralists to survive without cooperative labour investment and help from other households

By viewing cooperative herding groups as the building blocks of nomadic societies, COMPLEXITY aims to increase our understanding of the evolution of political complexity based on a new theoretical explanation of pastoral political organisation.


COMPLEXITY adds to state of the art through three steps.

While cooperative herding has been documented, previous studies have been based on single case studies.

The preliminary extent of cooperative herding groups.

Evidence is also fragmented, and little systematic attempts have been made to understand general patterns of pastoral cooperation.

The first step of COMPLEXITY is thus to cross-culturally analyse and document the prevalence of cooperative herding groups by using the existing ethnographic literature and a cross-cultural database

This will be used to select four field sites in Africa and Inner Asia: 

Study design where the overall starting point is to select two communities at two sites within each region. Arrows indicate levels of comparison undertaken in the project: between regions; between sites; and between communities. Coloured areas on the map indicate the already documented presence of herding groups while animal figures indicate the traditional Old World nomadic pastoral zones defined by the key cultural animal

Cooperation, performance and the rise of pastoral inequality

Understanding cross-cultural diversity and patterns in behaviour is a central goal of human behavioural ecology.

Nevertheless, the predominant view of cooperation is shaped by studies focusing on food sharing among foragers.

A conceptual overview of the domain, focus, problem, mechanisms and research load in evolutionary aspects of cooperation in anthropology. Food sharing has been a focus because it carries a cost for the giver: the giver must share parts of their food without knowing if the action will be reciprocated. Thus, sharing is a collective action dilemma, i.e., a situation where free-riders can thwart cooperation. Sharing labour is not riddled with the same dilemma: it is mutually beneficial and, thus, represent a coordination problem. Since individuals who share labour have common interests and share preferences, they always benefit from cooperation. Also referred to as mutualism, coordination has been argued to be a better representation for many situations of human cooperation. Nevertheless, they have been viewed as less interesting and trivial than collective action dilemmas: when everyone benefits from collective action, the cooperative solution should be obvious.

In contrast, less focus has been placed on cooperative production, the primary form of cooperation among pastoralists.

Consequently, COMPLEXITY’s second step is to use field studies to comparatively investigate to what degree pastoral cooperation is structured by evolutionary factors and investigate how cooperation affects pastoral performance.

The evolution of political complexity: from small-scale cooperative group to empires?

There is also a view that livestock, as the primary source of wealth, limits the development of inequalities, making pastoralism unable to support complex organisations.

However, the Gini coefficient for reindeer in Norway indicates that wealth in livestock is more unevenly distributed than for Norway in general (see this preprint   

Temporal trends in wealth inequality measured as reindeer numbers for (A) the Saami reindeer husbandry in Norway and (B) the Saami reindeer husbandry in the North and South (Fig 1.). The Gini coefficient ranges from 0 (perfect equality; everyone owns equally) to 1 (perfect inequality; one individual owns everything). Data for Gross Domestic Product (GDP) for Norway downloaded from Statistics of Norway ( See preprint for details.

Since we cannot observe the history of nomadic empires, COMPLEXITY’ will model if, for example, livestock as wealth can generate inequalities resulting in hierarchical power structures.

The third step is thus to combine empirical data with Agent-Based Modelling, to investigate whether cooperative herding groups can be considered prototypes for more complex organisations.

The funding makes it possible to hire 2 postdocs and 2 Phds working alongside me in Tromsø!

So stay tuned for job openings!