Analyse gender in music psychology from journal publication data

Authors

Tuomas Eerola

Anna Czepiel

Published

August 1, 2025

Gender analysis of the authors in music psychology journals since 2000. The journals included are Musicae Scientiae, Psychology of Music, Music Perception, Journal of New Music Research, and Music & Science and the data been obtained in June 2025 from Scopus.

1 Diagnostics

source('scripts/load_scopus_datasets.R') # Creates full_names dataset

Entries in the merged database: 3926 Entries in the author-expanded database: 9922 Entries in the author-expanded database after filtering editorials etc: 9662 Entries in the author-expanded database after filtering empty: 9651

source('scripts/attribute_country.R') # Add country affiliations

Entries in the author-expanded database after author affiliations: 9630

source('scripts/attribute_gender.R') # Adds gender attributions (precalculated with API)

Gender	n	percentage
ambiguous	32	0.4
female	3701	40.6
male	5365	58.8
unknown	27	0.3
Total	9125	100.1

Entries in the author-expanded database after filtering books/unattributed: 9066

source('scripts/name_gender_fixes.R') # Fixes the gender attribution of some names manually

Manual fixes

source('scripts/create_keys.R') # Add keys for authors and study+author

Single authors count: 778 Single + last authors count: 3373 Unique authors count: 5312 Unique countries count: 63

source('scripts/clean_citations_and_OA.R') # Process citations and OA status
source('scripts/attribute_gender_diagnostics.R') # Process citations and OA status

Unique studies: 3373

Unique Entries as studies and author combinations: 9066

Number of rows: 9066

JOURNAL	n	percentage
Journal of New Music Research	1496	16.5
Music Perception	1845	20.4
Music and Science	900	9.9
Musicae Scientiae	1524	16.8
Psychology of Music	3301	36.4
Total	9066	100.0

Confidence of gender attribution by the API:

Prop. over .90 conf. = 0.893

Prop. over .95 conf. = 0.867

Prop. under .55 conf. = 0.01

API: Gender probability means/medians.
Gender	M	Md
female	0.96	1
male	0.97	1

Citations across gender.
Gender	M	Md	LCI	UCI
female	19.81	9	18.73	20.88
male	22.24	10	21.24	23.24

Citations (t-test)
estimate	estimate1	estimate2	statistic	p.value	parameter	conf.low	conf.high	method	alternative
-2.43184	19.80861	22.24045	-3.254233	0.0011415	8416.543	-3.896703	-0.9669776	Welch Two Sample t-test	two.sided

Citations (Wilcox-test)
statistic	p.value	method	alternative
9392423	6.16e-05	Wilcoxon rank sum test with continuity correction	two.sided

Gender Distribution
est	lwr.ci	upr.ci
0.402	0.392	0.413
0.598	0.587	0.608

source('scripts/export_gender_data.R')

2 Summarise

source('scripts/summarise_gender.R') # different summaries

Gender	n	percentage
female	3647	40.2
male	5419	59.8
Total	9066	100.0

Number of coauthors:

median: 2 mean: 2.688 sd: 1.77 max: 34

Warning: Removed 2 rows containing missing values or values outside the scale range
(`geom_bar()`).

3 Quantify authorship types, citations and open access

source('scripts/quantify_authorship.R') # use Odds

Female authorship odds ratios by authorship type.
name	Odds_ratio	CI_low	CI_high
Single	0.905	0.778	1.052
First	1.408	1.284	1.544
Coauthor	0.997	0.913	1.090
Last	0.733	0.667	0.806

5-year growth rate of female authorships
Type	AAGR
First	12.15
Coauthor	-10.81
Last	-9.89

source('scripts/citations.R')           # Citations and gender
print(knitr::kable(citestats_all, digits = 2, caption = 'Citations across all authors'))

Citations across all authors
Gender	Md	M	Q75	CI_lower	CI_upper
female	9	19.81	22	9	10
male	10	22.24	27	9	10

print(knitr::kable(stats_all))

statistic	p.value	parameter	method
16.05391	6.16e-05	1	Kruskal-Wallis rank sum test

source('scripts/open_access.R')         # OA and gender
print(knitr::kable(author_OA, digits = 2, caption = 'Open access across all authors'))

Open access across all authors
Odds_ratio	CI	CI_low	CI_high	Type
1.49	0.95	1.29	1.73	First
1.06	0.95	0.92	1.23	Co
0.86	0.95	0.72	1.02	Last

4 Geographical

source('scripts/country_table.R') # OK

#source('scripts/visualise_gender.R') # OK

Female author odds ratios across continents.
Continent	N	Odds_ratio	CI_low	CI_high
Europe	4985	0.82	0.75	0.89
Americas	2356	1.12	1.02	1.23
Asia	931	0.89	0.78	1.02
Oceania	742	1.66	1.43	1.93
Africa	52	0.91	0.52	1.59

4.1 Keywords and gender

source('scripts/count2category.R') 
source('scripts/keyword_analysis.R')

[1] "Nurturing keywords/topics:"
[1] 0.1291887