Summary 2025
2025 comprises 57 publications, an increase of 6 % compared to 2024. 46 of 85 researchers appear for the first time in the dataset. Open access (86 %) exceeds the period average (73 %). Data from DiVA.
Key indicators summarise the report’s central metrics. All values are calculated from the underlying dataset and refer to the full period unless otherwise stated. Percentages (peer-reviewed, Open Access, international collaboration) are calculated as a share of total publications per year.
Percentage change is not shown when the base value is below 10 units, as small base values produce statistically unstable percentages (Hicks et al. (2015), principle 8; cf. CDC rule for n < 16). Absolute values are shown instead.
Insights
During the period 2010-2025, the
compound annual growth rate (CAGR) was +17.6%. The trend is
increasing (statistically significant; p < 0.05).
Mann
(1945);
Sen
(1968) The following years had unusually high publication activity:
2023.
Insights 2025
Focus year 2025 had 57 publications, increase 6% compared to 2024.
Insights
The peer-reviewed share decreased from
60 % to 53% [40%–65%] (7.4 percentage points) during 2010–2025.
Insights 2025
In 2025, 53% of publications were peer-reviewed, in line with the period average (53%). The most common type was konferensbidrag (42%). Compared to 2024, the peer-reviewed share decreased by 3 percentage points. Citation data is available for 52% of artikel i tidskrift, but only 0% of licentiatavhandling, monografi.
505 publications (92%) scientific, 42 publications (8%) other.
Older years (2010–2017) aggregated for readability. Full timespan available in data export.
Insights 2025
In 2025, articles were published in 11 unique journals (period avg:
8.5/year).
4 journals appear for the first time: Temenos (2),
Geography (1).
29 journals from 2022–2024 are absent in 2025:
Geografiska Notiser, Historisk Tidskrift.
Largest increase: Journal of Curriculum Studies (3 pub.
2025, snitt 0.5/år); Religion & Livsfrågor (2 pub. 2025, snitt
0.2/år).
Of 11 unique journals in 2025, 5 (45%) were classified
as NPI Level 2: Journal of Curriculum Studies, Temenos.
3 journals (27%) lacked NPI classification: Religion
& Livsfrågor, Journal of Social Science Education.
Journal articles in 2025 had an average field-weighted
citation impact (FWCI) of 3.26, based on 13 publications with citation
data. FWCI = 1.0 corresponds to the world average.
38% of journal
articles ranked in the top 10% most cited in their field (5 of 13 with
data).
The Norwegian Publication Indicator (NPI), also known as the Norwegian list, classifies publication channels into two levels. Level 2 (top ~20% per field) is considered the most prestigious channels. Level 1 covers other approved channels.
Insights 2025
In 2025, 73% were published in Level 2 channels, well above the period average (14%). Compared to 2024, the share increased by 73 percentage points. Notably, 81% of publications lacked NPI classification.
A high proportion of publications (≥10%) lack NPI classification. Common causes: missing ISSN in source data, channels outside the register (~40,000 journals), conference series, or recently launched journals. See the journal table for unclassified channels.
DORA mode is enabled for this report. Bifrost evaluates the report against the principles of DORA (2012) and CoARA (2022).
The report contains elements that are not compatible with DORA principle 1: “Do not use journal-based metrics as a surrogate measure of the quality of individual research articles.”
NPI level classification (Level 1/2) is shown in the report. NPI is a Nordic classification system that ranks publication channels by academic standing, i.e. a channel-based ranking that DORA advises against using as a quality surrogate. The classification is presented here as descriptive information about publication patterns, not as a measure of individual article quality.
Publication points (Norwegian model) are shown in the report. Publication points weight publications by channel classification (NPI level) and are used by Swedish higher education institutions for resource allocation. This metric uses publication channel as a proxy, a methodology that DORA principle 1 explicitly discourages for assessing individual researchers. The metric is presented here in a descriptive capacity (volume and distribution), not as a measure of individual research quality.
Researchers are listed below, sorted by scientific productivity.
Insights
The top 20% most productive researchers
account for 57% of publications (Gini 0.43, scale: 0 = even, 1 = fully
concentrated). Average number of co-authors increased from 1.7
(2010–2017) to 2.2 (2018–2025).
Insights 2025
With 85 unique researchers in 2025, the count was well above the period average (34.1 per year). Of these, 46 (54 %) were new to the dataset, suggesting high turnover among active researchers. The most productive researcher was Katarina Plank with 10 publications. The average was 0.7 publications per researcher, lower than the period average (0.9).
Network structure (clusters, clustering, centrality) is based on the full period 2010–2025. Collaboration volumes and basic metrics are also shown for focus year 2025.
Insights
16 research groups of roughly equal
size; no single cluster dominates. Each researcher collaborates with an
average of 3.4 others (a moderately connected network). Clear cluster
structure (Modularity 0.89); researchers primarily work within their own
group. The network is sparse: only 3.6% of all researcher pairs have a
direct collaboration link.
Insights 2025
In 2025, 70.2% of publications were co-authored (period average 50.5%). Average 2.6 co-authors per article (2.0 across the period). 144 new collaboration links appeared (pairs that had not collaborated during the previous 3 years). Publications with international collaboration had the highest citation impact (FWCI 6.89, n=34), compared to single author (FWCI 3.75, n=271).
Each node represents a researcher and each link a co-authorship. Colors indicate research groups (clusters) identified via modularity analysis. Node size reflects number of publications.
The co-authorship network is built from co-authored publications. Each node represents a researcher, and each edge is weighted by number of joint publications. Edge weights are normalized using association strength Van Eck et al. (2009) before clustering with the Louvain algorithm. Centrality measures: degree (number of collaborators), collaboration intensity (total co-authoring frequency), and bridge score (weighted betweenness using inverse weights) Newman (2004). Network density measures the proportion of realized vs. possible collaborations. Terminology: «Collaborators (avg)» = mean degree; «Clustering» = modularity Blondel et al. (2008).
Percentages are calculated on pairs where both authors have country data (544 classified of 548 total, coverage 99%). Of which 0 pairs where both authors lack institutional affiliation, 0 pairs where the institution could not be mapped to a country, and 4 pairs where one side lacks data.
‘Co-authored texts’ indicates the number of texts the author has written together with one or more co-authors.
Network statistics show central nodes in the collaboration network. Degree is the number of direct collaborations, while betweenness shows which authors act as bridges between different groups.
Insights 2025
Emerging networkers: Bellström, Peter; Alaqra, Ala Sarah; Vikström, Carina (+7) (researchers with no publications during the previous 3 years but at least 2 co-authored publications in the focus year). Broadest collaborators: Olsson, David (14); Bellström, Peter (10); Alaqra, Ala Sarah (10); Jakobsson, Martin (9); Bladh, Gabriel (9) (most unique co-authors in the focus year (at least 2 publications, at least 5 unique)). Most productive pairs: Backius, Stefan & Melin, Åsa (3); Borup, Jørn & Härkönen, Mitra (3); Borup, Jørn & Jacobsen, Knut A. (3); Borup, Jørn & Plank, Katarina (3); Härkönen, Mitra & Jacobsen, Knut A. (3).
The table covers the full period 2010–2025.
The first co-author listed is the one the author has written with the most times. ‘Number’ indicates the number of co-authored texts with the author. Up to four additional co-authors are listed, in descending order of co-authorship.
The table covers the full period 2010–2025.
Below is a visualization of the 16 different groupings in the dataset. The colors indicate different groups.
Adaptive visualization (large): 94 nodes / 158 edges shown in full (no filtering needed).
The visualization was restored to the unfiltered source network: the adaptive filters would otherwise have reduced it below the threshold for a meaningful display.
Researchers with a purple border were active in the focus year 2025.
Author names to the right; group ID to the left. You can see the size of the groups and the most common keywords of the groups in the tables that follow. A combination of search and sorting can be used to further explore group membership.
The chart compares the field-weighted citation impact (FWCI) for the co-authorship clusters identified through network analysis. Each publication is assigned to the cluster where most of its authors belong. FWCI = 1.0 corresponds to the world average. n is the number of publications in the cluster (shown on hover).
The table is limited to a) groups with more than 3 members; b) groups with at least one keyword in any publication; c) the ten most used keywords per group.
Unlike the co-authorship analysis, which maps collaboration through joint publications, this section reveals the academic networks that emerge through dissertation supervision and opposition. Supervisors and opponents active at multiple institutions form informal knowledge bridges between organizations — relationships rarely captured by traditional bibliometric measures but which can reveal important patterns in academic knowledge transfer.
Insights
17 researchers have supervised or
opposed across institutional boundaries. Strongest connection:
University of Gothenburg – Karlstad University (Connection strength: 2).
Based on 94.4% of dissertations with identifiable supervisors.
The supervisor/opponent network is separate from the international collaboration map. The map is based on co-authorship between author affiliations, while supervisor/opponent relations are shown in the network below.
The network is based on supervisor and opponent relationships extracted from SwePub records. Connection strength is calculated as (number of supervisions × 2) + (number of oppositions × 1). The weighting (2:1) is a Bifrost convention reflecting that supervision is a longer and deeper collaborative relationship than opposition. The method lacks established bibliometric practice; it was developed specifically for Bifrost.
The supervisor:opponent weighting (2:1) is a Bifrost convention to reflect the supervisor’s greater role in the dissertation process. This is not established bibliometric practice.
Insights
47 institutions contribute. Karlstads
universitet dominated with 535 publications (76 %). Next largest:
Göteborgs universitet (19), Linköpings universitet (16). Concentration
index (HHI): 0.577.
Insights 2025
In 2025, 16 institutions contributed (period average 9). Karlstads universitet dominated with 56 publications (64 %) in the focus year (74 % across the period). Next largest: Helsingfors universitet (6), Göteborgs universitet (5). 5 institutions appeared that had not published during the previous 3 years.
Overview of international collaboration based on co-authorship and affiliations in publications.
Insights
Full period 2010–2025. 9 länder
representerade i samarbeten. Finland, Storbritannien och Norge är
vanligast. 6.2 % av publikationerna har internationella medförfattare —
ökning från 3 % (2010–2017) till 7 % (2018–2025).
Insights 2025
Under 2025 var 6 länder representerade (periodssnitt 3). 16 % av publikationerna hade internationella medförfattare (periodssnitt 6 %).
Based on co-author affiliation country.
Institutions with a purple border were active during the focus year 2025.
Insights:
The network comprises 29 institutions
with 47 collaboration relationships. The strongest collaboration is
between University of Gothenburg and Karlstad University (19
co-publications). Karlstad University has the most collaboration
partners (21).
Focus year 2025:
16 institutions were active during the focus year. 5 new institutions appeared (Inland Norway University of Applied Sciences, Aarhus University, University of Bergen, …). Strongest focus year collaboration: University of Helsinki and Karlstad University (6 co-publications).
The collaboration network on the map is based on the full period 2010–2025.
The map primarily shows co-authorship between institutions. Supervisor/opponent links are shown as separate network relations and may be fewer, because only records with clear institutional affiliation can be included.
Insights
Social Sciences dominates (59 %).
Subject breadth is stable (2010–2025, H: 0.69 → 0.74). Research is
markedly interdisciplinary — it combines taxonomically distant subject
areas. Rao-Stirling: 0.696 (where 0 = single discipline, 1 = maximum
diversity). Based on 4 HSV main areas (Swedish classification).
Rao-Stirling
(Stirling, 2007)
Shannon H (evenness index) measures how evenly publications are distributed across subject areas. A value of 1.00 means perfect evenness; lower values indicate dominance by individual areas. Rao-Stirling measures interdisciplinarity by weighing both the distribution and the taxonomic distance between subject areas according to the Swedish classification system. The scale ranges from 0 (all publications in one subject) to 1 (maximum spread across distant subject areas).
The figure shows the full period 2010–2025.
Insights 2025
In 2025, Social Sciences dominated (50.0% of publications, period average 59.2%). Agricultural and Veterinary sciences was entirely absent in the focus year (period average 0.2%).
Proportion of total publications per year (%). Note that a publication may belong to multiple categories.
Insights 2025
In 2025, Educational Sciences dominated (39.7% of publications, period average 44.7%). Philosophy, Ethics and Religion was over-represented (21.9% vs period average 10.7%). New categories in the focus year: Computer and Information Sciences. The following were entirely absent in the focus year: Other Humanities (period avg. 4.3 %); Economics and Business (period avg. 0.6 %).
Proportion of total publications per year (%). Note that a publication may belong to multiple categories.
mathematics; learning
Insights
Broad keyword profile — no single term
dominates (HHI: 0.0024 — Herfindahl-Hirschman Index, where 0 = perfectly
even distribution, 1 = one term dominates entirely). Most common is
“history education” appearing in 6.6 % of publications, across a total
of 969.
The word cloud shows keywords from the focus year’s (2025) publications. Other analyses below are based on the full period 2010–2025.
Colors indicate frequency quantiles within this dataset.
Red: Highest frequency (8.8-7.4%); Blue: High frequency (7.4-6%); Green: Medium frequency (6-4.6%); Orange: Low frequency (4.6-3.2%); Gray: Lowest frequency (3.2-1.8%)
Colors indicate frequency quantiles within this dataset.
Red: Highest frequency (6.6-5.32%); Blue: High frequency (5.32-4.04%); Green: Medium frequency (4.04-2.76%); Orange: Low frequency (2.76-1.48%); Gray: Lowest frequency (1.48-0.2%)
Trends below are based on the full period 2010–2025.
Declining keywords: historical consciousness, religious education
No rising trends were identified. Below are deep-dive insights for declining keywords instead. These may indicate subject areas decreasing in relevance or research interest.
The following keywords had periods of high activity in the past but have since declined. The analysis shows when they peaked, what drove the interest, and how activity has evolved since.
Burst period: 2015–2016 (moderate burst)
Peak year: 2016 (4 pubs.)
Driving actors during period:
Co-varying keywords: religionsdidaktik, sverige, sweden
Current status: Potentially declining
The heatmap shows how often keywords co-occur in the same publications. Association strength Van Eck et al. (2009) normalizes co-occurrence by the product of the individual keyword frequencies. Red asterisks (✱) in the upper-right corner of cells mark statistically significant co-occurrences (p < 0.05).
Keywords that frequently co-occur in the same publications form thematic clusters. The table below summarizes the clusters; the interactive graph shows the relationships visually.
The network diagram is based on all publications in the period 2010–2025 (insufficient data for focus year only).
The network diagram shows how keywords relate to each other based on co-occurrence in publications. Larger nodes mean more frequent keywords. Lines show co-occurrence. Colors indicate thematic clusters identified using the Leiden algorithm (Traag et al., 2019).
The frequency of individual words in the dataset as a whole. Words have been taken from title, abstract, and keywords. “Frequency” is total uses, including the number of mentions in the same text, while “publications” is the number of unique texts where the word appears.
Word frequencies below are based on all publications in the period 2010–2025.
Insights 2025
The 5 most common words in the focus year’s publications (2025) are: “education” (28%), “social” (25%), “school” (21%), “swedish” (21%), “history” (19%). Compared to the full period (2010–2025), these words have changed in relative frequency. Note that geographic markers such as “swedish” are common in academic metadata and reflect the national affiliation of publications rather than the research topic.
Notice: The dataset contains 8953 rows. For best performance, only the 8000 with the highest frequency are displayed in the table.
If you want to examine the frequency of some specific words more closely, enter them in the variable ‘to_stem’.
Trends are based on the full period 2010–2025. Focus year breakthroughs and changes are shown at the end of this section.
These trends are indicative and complement the keyword analysis above.
Methodological note: Word frequency analysis is based on individual words extracted from title, abstract, and keywords. Unlike author-selected keywords, individual words can be noisier and more ambiguous — for example, the word ‘system’ may appear in both technical and social science contexts, while the keyword ‘adaptive systems’ is more precise. Stricter thresholds are used (minimum 10 occurrences, correlation > 0.5) and academic stopwords are excluded.
Rising/declining shows trends over time (Spearman correlation). New/disappearing shows lifecycle — when words started or stopped being used.
No statistically significant trends were identified among the most common words.
Thematic breakthroughs 2025 2025
These words suddenly became more common during the focus year compared to their historical level, which may indicate emerging research directions.
olika, dimensions, finns, gäller, nordic, religious, också, första, documents, bygger
…and 22 more words
Words with the largest change in share of publications between the focus year and the previous year.
Rising: olika, nordic, religion, social, del, transformation, ge, individual, kommer, age
Declining: teaching, learning, thinking, disciplinary, svensk, history, narrative, narratives, basic, bergslagen
The year-on-year comparison is based on two individual years and is sensitive to random variation. Interpretive caution is recommended.
The analysis below summarises citations in the dataset and highlights trends over time, by researcher, and for the most cited works.
The publication information has been retrieved from DiVA and enriched with citation data from OpenAlex.
The annual publication count has changed positively over the period 2010–2025 (CAGR based on 15 complete calendar years, current year excluded). This analysis covers 547 publications from DiVA for the period 2010–2025. Citation data is available for 22 % of publications.
Generated from period data
Note:
Citation data are cumulative totals
retrieved from OpenAlex — they show how many times each publication has
been cited since it was published. Publications from more recent years
have had less time to accumulate citations, which should be considered
when comparing across years. The citation analysis covers the entire
period, not just the focus year — unlike other sections.
On comparability:
Field-normalized percentiles
from OpenAlex (normalized by year, work type, and subfield). 57
publications (10%) are from the last 2 years and may have understated
percentiles.
Self-citation
Citation counts in this report
include both external citations and self-citations. The self-citation
share may be substantial for individuals and small datasets. See the
method card below for details.
Hicks
et al. (2015)
FWCI (Field-Weighted Citation Impact) measures how much a publication has been cited compared to what is expected for that type of research, publication year, and subject field, internationally. FWCI = 1.0 is the expected value: the typical number of citations for similar publications globally. Below 1.0 means fewer citations than expected; 1.5 means 50% more; 2.0 means twice as many. Normalisation by field is necessary because citation cultures differ markedly. Medicine cites far more frequently than mathematics, making direct comparisons misleading. Data comes from OpenAlex. Note that a few highly cited publications can pull the figure up substantially, and the measure requires sufficient coverage (at least 10 publications with citation data).
PP(top 10%) measures the share of a group’s publications that rank among the top 10% most cited in their subject field and publication year, internationally. The reference value is 10%: if a group published at a perfectly average level, exactly 10% would fall into the top bracket. Above 10% means a larger share than expected achieves high citation impact; below 10% means the opposite. The measure is field-normalised, meaning each publication is compared with others in the same field and year. This avoids the problem that, for example, medical research is generally cited more than mathematics. Data comes from OpenAlex. Note that small datasets can produce large random fluctuations, and recently published articles often lack sufficient citation history for a fair ranking.
Citation coverage:
Citation data could only be
retrieved for 23% of publications (128 of 547). Citation indicators
should be interpreted with great caution as they represent a small
portion of the dataset.
Citations show how often other researchers reference these publications in their own work. High citation counts indicate that the research has had impact within its field.
FWCI (Field-Weighted Citation Impact) is the ratio of actual to expected citations, normalised by year, work type, and subject field (OpenAlex subfield). FWCI = 1.0 means the publications are cited in line with the world average for their field. Unlike percentile measures, FWCI is sensitive to individual highly cited publications — two units with the same PP(top 10%%) may differ in FWCI if one has a few very highly cited works.
Mean FWCI: 4.46
Based on 119 publications with FWCI data
The stability interval (95%) indicates the likely range of values if the publication set were to change. Computed via BCa bootstrap (bias-corrected and accelerated) at the publication level with 2,000 replicates. Terminology and confidence level follow the CWTS Leiden Ranking; the BCa variant (rather than simple percentile bootstrap) is methodologically stronger. Not shown when the underlying data are too sparse (FWCI: n < 10; PP(top 10%) and PP(top 1%): n < 30) or when percentile coverage is low (< 50%). Waltman et al. (2012), DiCiccio et al. (1996)
FWCI: 4.46 (uncertainty interval 3.37–6.09)
No stability interval for Top 10%: percentile coverage 21.8% (requires
at least 50%).
No stability interval for Top 1%: percentile coverage
21.8% (requires at least 50%).
The chart shows the proportion of publications in different citation percentile bands per year, based on field-normalized percentiles from OpenAlex. Publications from the most recent 2 years are excluded due to incomplete citation accumulation.
The chart compares the average field-weighted citation impact (FWCI) for publications with different Open Access statuses. The reference line marks the world average (FWCI = 1.0). FWCI requires at least 10 publications per category.
The chart compares citation impact for publications with international collaboration, domestic collaboration, and single-author publications. International collaboration is defined as publications with authors from more than one country.
The boxplot shows the distribution of field-weighted citation impact (FWCI) per publication year. The dashed line marks the world average (1.0). Publications from the most recent 2 years are excluded.
Insights
547 publications have a total of 1 359
citations (median 0.0/publication, avg 2.5/publication). 83.2 % are
uncited. Most cited (110 cit): Gericke, Niklas;Hudson,
Brian;Olin-Scheller, Christina;Stolare, Martin (2018). Powerful
knowledge, transformations and the need for empirical studies across
school subjects. London Review of Education. https://doi.org/10.18546/LRE.16.3.06 The field-weighted
citation impact (FWCI) averages 4.94 (based on 99 publications). The
trend is decreasing.
The chart shows how citations are distributed across publication years. Note that older publications have had more time to accumulate citations.
Grey bars mark publications from the last two years, whose citation data are incomplete — they have not had time to accumulate citations to the same extent as older publications.
The chart shows the field-weighted citation impact (FWCI) for the most cited researchers, with a three-year rolling average. The dashed line marks the world average (FWCI = 1.0). Includes researchers with at least 5 publications spanning at least 3 years.
The OA analysis is based on 128 publications with DOI matched against OpenAlex (23% of 547 total). 416 publications lack DOI and are therefore not included in OA statistics.
Insights
The OA share went from 100 % to 86%
(14.3 percentage points) during 2010–2025. Hybrid accounted for the
largest increase (+17.3 percentage points). Green OA accounts for 7.8 %
of all publications — available via open repository after an embargo
period (typically 6–12 months); more recent publications may not yet be
freely accessible. Diamond OA (no fees for authors or readers) accounts
for 26.6 %.
Insights 2025
The open access share in 2025 was 86% (period average: 70%)
An
increase of 7 percentage points compared to 2024
Distribution 2025:
28% gold, 6% green, 39% hybrid
Note:
125 of 131 publications with DOI were
matched against OpenAlex and assigned OA status (95.4%). OA status is
sourced from OpenAlex (based on Unpaywall). OA status may be
retroactively classified — a publication that is freely available today
may have been closed at the time of publication. The trend should
therefore be interpreted with caution, especially for older
publications. Green OA classification is based on the presence of a
version in an open repository, regardless of whether any embargo period
has expired — the Green OA share may therefore be overestimated for more
recent publications.
The first doctoral thesis in the dataset is from 2011, Kommunala ideal och politisk verklighet. : En jämförande fallstudie av frisinnad politisk organisering i Filipstad och Skövde, ca 1880-1920. by Forsell, Anders. From then until 2025, a total of 18 theses have been registered. Of these, 10 are doctoral theses and 8 are licentiate theses.
A complete list of the search results. Initially sorted by year (descending) and author (ascending). Change the order at the column header. Search can be done over all displayed fields.
2025 Export files contain only focus year (2025) publications (57 items).
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