# Authorship Conflicts in Academia: an International Cross-Discipline Survey

Elizaveta Savchenko  Ariel Rosenfeld  Department of Information Science, Bar-
Ilan University, Ramat-Gan, Israel

###### Abstract

Collaboration among scholars has emerged as a significant characteristic of
contemporary science. As a result, the number of authors listed in
publications continues to rise steadily. Unfortunately, determining the
authors to be included in the byline and their respective order entails
multiple difficulties which often lead to conflicts. Despite the large volume
of literature about conflicts in academia, it remains unclear how exactly
these are distributed over the main socio-demographic properties, as well as
the different types of interactions academics experience. To address this gap,
we conducted an international and cross-disciplinary survey answered by 752
academics from 41 fields of research and 93 countries that statistically well-
represent the overall academic workforce. Our findings are concerning and
suggest that conflicts over authorship credit arise very early in one’s
academic career, even at the level of Master and Ph.D., and become
increasingly common over time.

Keywords: Academic conflicts, Credit distribution; Co-authorship; Advisor-
advisee relationship; Academic collaboration.

##  1 Introduction

Scientific collaboration has become a prominent feature in modern science [1].
Consequently, sole authorship (one publication—one author), which was a common
practice until the twentieth century [2], has transformed over time to co-
authorship (one publication-multiple authors) [3], with an ever-increasing
number of authors lists on papers [4, 5, 6].

Unfortunately, determining which authors should be listed in the byline and
their respective order encompasses multiple challenges [7, 8, 9, 10].
Specifically, the inherent competition for jobs, promotions, grants, and
recognition amongst researchers is often associated with self-interested
behavior which may lead to conflicts over these two authorship credit
distribution questions (authorship credit conflicts, for short) [11, 12, 13,
14]. Naturally, as the number of parties involved in collaborative research
work increases, the magnitude and intensity of these conflicts increase
proportionally [15, 16, 17].

In order to mitigate these and similar conflicts and bring about a fair and
transparent authorship credit distribution, journals have adopted formal
criteria to define which contributors should be listed and, in some cases,
even determine their appropriate order [18]. Several common criteria include,
but not limited, to
ICMJE-2009111http://www.ease.org.uk/sites/default/files/ease_guidelines-
june2011c.pdf, EASE-2011222http://www.icmje.org/ethical_1author.html,
CSE-2012333http://www.councilscienceeditors.org/files/public/entire_whitepaper.pdf,
and COPE-2008444http://publicationethics.org/files/u2/All_flowcharts.pdf.
These criteria generally agree that authorship credit should be limited to
individuals who have contributed in a meaningful and substantive way to its
intellectual content [19]. However, they usually adopt somewhat vague or
ambiguous terms that can lead to different interpretations. For example, it is
not clear what is the minimal threshold for contribution to consider one’s
contribution to be meaningful enough to be listed as an author. Moreover, it
is rather simple to find cases in which the different criteria disagree [20,
21]. In parallel, several other solutions have been proposed to allow authors
to better convey the role each party played in the collaboration work and the
credit that should be associated with each co-author [22, 23, 24]. One popular
solution is the CRediT (Contributor Role Taxonomy) system which requires
authors to report the roles and contributions of each author separately based
on fourteen different contribution types [25]. Other common solutions to
indicate varying levels of contributions include multiple first authors (i.e.,
co-first author) and multiple corresponding authors (i.e., co-corresponding
authors) [26]. Many consider these and other similar solutions to be important
steps in the right direction [27].

Unfortunately, there is only a very limited understanding of the extent and
characteristics of the underlying phenomena today [28, 29, 30]. Specifically,
existing literature investigating academic conflicts has predominantly
considered individual research fields, countries or very specific types of
conflicts in isolation [31, 32, 33, 34, 35]. As such, the practical relevance
of the proposed solutions, and perhaps the future development of novel more
advanced solutions, could be significantly improved by considering more
comprehensive data that accounts for multiple fields of study, nations, and
types of authorship conflicts. In this work, we seek to fill this gap in
knowledge by reporting the results of an international cross-discipline survey
targeted at estimating and characterizing authorship credit conflicts in
academia. From a methodological standpoint, by asking researchers to
anonymously report their prior experiences in authorship conflicts, we are
provided with a unique opportunity to reveal data that is not directly
observable otherwise. Specifically, examining and analysing published outputs
of collaborative work, which is the common methodological instrument practiced
by prior work in this context [36, 37, 38, 39], can only attest to the final
resolution of conflicts, and only if one had actually occurred. Unique to our
survey is the distinction between seemingly symmetrical and obviously
asymmetrical relations. Specifically, our study focuses on two standard types
of academic relations: one between colleagues (i.e., a seemingly symmetrical
relation) and one between an academic advisor and an advisee (i.e., an
inherently asymmetrical relation). To the best of our knowledge, authorship
conflicts in the advisor-advisee relationship have yet to be examined in prior
literature and thus contributes a novel perspective on the matter.

The remainder of this article is organized as follows: Section 2 presents the
data gathering and statistical analysis approaches. Then, Section 3 outlines
the results followed by Section 4 which summarizes, interprets, and discusses
the results in the wider context.

##  2 Methods and Materials

From a methodological standpoint, we ask the scholars themselves about their
behavior and experience. To gather the required data, we utilize an online
survey approach. The survey was developed, distributed, and analysed as
detailed below. Fig. 1 shows a schematic view of the process.

Figure 1: A schematic view of the study’s methodological process.

###  2.1 Survey Development

Inspired by previous studies which have developed surveys to study scholars’
behaviors and preferences [40, 41, 42, 43, 44], we designed a 24-item closed-
form questionnaire consisted of four parts: First, socio-demographic questions
(6 items); Second, work and publication patterns-related questions (3 items);
Third, questions pertaining to potential authorship credit distribution
conflicts with one’s Masters and PhD advisor(s) (6x2=12 items); Last,
questions pertaining to potential authorship credit distribution conflicts
with one’s peers (3 items). The full set of items, as well as their possible
closed-form answers, is provided in the Appendix.

The rationale of the survey, as presented to the respondents at the beginning
of the survey, stated that This survey intends to examine the extent and
characteristics of disagreements in academic co-authorship.. We chose to use
the term disagreement instead of conflict in this context in order to avoid
inducing negative connotations.

###  2.2 Distribution

In order to reach as many researchers as possible we used an online
questionnaire in the form of a Google form. All responses were kept
confidentially and anonymously as clearly stated to the participants at the
beginning of the questionnaire. The data was collected between July 2022 and
November 2022. During this time, emails, as well as social media messages in
the academic social media platform
ResearchGate555https://www.researchgate.net/ inviting researchers to
participate in the survey, were sent. The targeted researchers were chosen
manually based on their affiliation country and field of research, as self-
evident or self-declared in their email’s signature, ResearchGate profile, or
personal website in order to obtain an adequate representation of the
worldwide research workforce. Overall, 15,362 inventions were sent and a
sample of 752 researchers from 93 countries and 41 fields of research was
obtained ($4.89\%$ response rate). All participants had to acknowledge that
they actively conduct academic research in order to avoid non-relevant samples
and provided their informed consent. The representativeness of the obtained
sample is established next. The study was approved by the corresponding IRB.

###  2.3 Representative Sample

We first establish that the obtained sample is, indeed, representative of the
studied population. For this purpose, one has to show that the sampled data
satisfies two primary conditions: 1) it is large enough, and 2) the measurable
parameters’ distribution that is known (or approximated) for the entire
population is statistically indistinguishable from these of the sample [45,
46, 47].

First, under the assumption that all socio-demographic measures used in the
questionnaire are normally distributed, we conducted a sample size power test
[48], assuming the overall number of academics is 10.26 million666The UNESCO
Science Report[49] has estimated 7.8 million researchers at 2013 with 21%
grows over six years, from 2007. We extrapolate these numbers by assuming that
the growth rate is constant and computed a linear projection to 2022 by
multiplying $7.8$ by $1.315$. and a required p-value of $0.01$. From this
configuration, 667 or more samples are sufficient. Second, we analysed 22 past
research papers which have used, presumably, representative samples of the
academic community. For each paper, we manually extracted the sample size and
computed the mean and standard divination to be $429\pm 518$ with a median of
$257$. A full description of the papers used in this analysis and their sample
sizes are provided in the Appendix. Taken jointly, our sample size is larger
than the minimal number of required participants according to the power test,
$1.75$ times larger than the average sample size and $2.92$ times larger than
the median one.

For the second condition, we used the age, gender, and national affiliation
distributions of academics in the world as reported by the UNESCO Science
Report [49]. We performed a Kolmogorov–Smirnov test [50] between the entire
population’s characteristics and our co-distribution of these parameters,
obtaining a p-value of $0.038<0.05$. Thus, the population is statistically
well represented by our sample.

###  2.4 Analytical Approach

The comparison of subsets of the data which fulfill some condition, e.g., male
vs female respondents, is conducted using the $\chi^{2}$ test [51]. When more
than two groups are compared a $\chi^{2}$ test is conducted, followed by a
post-hoc $\chi^{2}$ tests with Bonferroni Adjustment [52]. All statistical
analysis was conducted using the Python programming language [53], version
3.7.5. Unless stated otherwise, significance is determined at $p<0.05$.

Due to a large number of possible national affiliations, for our analysis, we
grouped them into continents following the definition of the OECD
(Organisation for Economic Co-operation and Development)777For more
information please refer to https://www.oecd.org/about/document/ratification-
oecd-convention.htm. In a similar manner, the fields of research were grouped
into five disciplines - Exact, Social, Nature, Engineering, and Medicine
sciences, following UNESCO’s methodology [49].

##  3 Result

Our analysis consists of four parts: First, we report the main socio-
demographic characteristic of our sample. Then, we analyze the extent and
characteristics of conflicts by considering the advisor-advisee and peer
relationships, separately. Last, we consider the interaction between the two
analyses – that is, the possible link between one’s conflicts as an advisee
and one’s subsequent conflicts with his/her peers.

###  3.1 Socio-Demographics

Our sample consists of 752 academics, $517$ ($68.8$%) of whom are male and
$233$ ($31$%) are female (2 participants opted not to identify their gender).
In terms of age: 3.7% are below 25 years old, 21.7% are 26-35 years old, 30.2%
are 36-45 years old, 24.3% are 46-55 years old, 13.8% are 55-65 and 6.3% are
above 65 years of age. The participants vary in their most recently obtained
academic rank as follows: 0.9% hold only a Bachelor’s degree, 7.6% hold a
Master’s degree, 51.2% hold a PhD or MD, and 40.3% have reached a rank of
Professor (either associate, full or emeritus). Similarly, the participants
are primarily affiliated with $93$ different countries all across the world
with the three most prominent ones being the United States of America (USA)
($9.3$%), United Kingdom ($8.6$%), and Israel ($7.3$%). The participants also
reported their main field of research to span over $41$ different research
subjects with the three most prominent ones being Mathematics ($7.4$%),
Economics ($6.8$%), and Informatics ($6.4$%). Considering the participants’
academic age (i.e., years passed since their first academic publication),
34.2% report 20 or more years, 24.3% report 10-20 years, 20.9% report 6-9
years, 13.8% report 3-5 years and the remaining 6.8% report less than 3 years.

###  3.2 Advisor-Advisee Conflicts

For the following analysis, we omitted the responses of those who reported
having no advisor for the relevant period. For example, individuals who
pursued a direct PhD were omitted from consideration under the Master’s period
analysis. Overall, 26 responses (3.3%) were omitted for Master’s period
analysis and 5 responses ($<$1%) were omitted from the PhD’s period analysis.
Overall, in our data, the ratio between those who had a single advisor and
those who had multiple advisors is 4.8 (Masters) and 2.4 (PhD), the ratio
between those who had a Professor as their main advisor and those who had not
is 2.3 (Masters) and 15.9 (PhD), and the ratio between those who had a male
primary advisor and those who had a female one is 5.5 (Masters) and 9.9 (PhD).
Next, we consider each of the examined characteristics of the
advisor(s)-advisee relationship and the associated conflict prevalence as
reported in the two relevant questions of the survey – Have you ever had a
disagreement with your Masters’ advisor(s) over authorship credit distribution
(i.e., who should get authorship credit or how the author byline should be
ordered) and Have you ever had a disagreement with your PhD’s (or MD)
advisor(s) over authorship credit distribution (i.e., who should get
authorship credit or how the author byline should be ordered). Table 1
summarizes the main results.

Starting by considering all respondents together, 10.5% have reported having
at least one authorship conflict with their Masters’ advisor(s), whereas 16.3%
reported the same for their PhD advisor(s). Statistically, respondents are
more likely to report a conflict during their PhD with their advisor(s)
compared to their Master’s period, $p<0.01$. In addition, respondents who had
a conflict with their Masters’ advisor(s) are significantly more likely to
have a conflict with their PhD advisor(s) as well, 11.4% vs 17.2%, $p<0.05$.

Considering the number of advisors, the results are mixed. First, having more
than a single Masters advisor is associated with a significant increase in
conflict prevalence (19.6% vs 8.7%) whereas having more than a single PhD
advisor is associated with a significant decrease in conflict prevalence
(17.6% vs 13.8%), both at $p<0.05$. In addition, having a single PhD advisor
is associated with a significantly higher conflict prevalence compared to
having a single Masters advisor, $p<0.01$.

In four out of the five examined disciplines (Exact, Social, Nature and
Medicine) the prevalence of conflicts with one’s PhD advisor(s) is higher
compared to that with Masters advisor(s). However, the difference is only
statistically significant for the Exact sciences for which the relevant
respondents reported 17.1% conflict prevalence with their PhD advisor(s)
compared to 11% conflict prevalence with their Masters advisor(s), $p<0.05$.
For the Engineering discipline, the opposite result is encountered with more
conflicts encountered during the Masters period, yet the difference is not
statistically significant.

Turning to the issue of gender, we see that both male and female respondents
are significantly more likely to report conflicts with their PhD advisor(s)
compared to their Masters advisor(s). Specifically, 11.3% and 15.8% of all
male respondents report a conflict with their Masters and PhD advisor(s),
respectively, $p<0.01$. Similarly, 8.2% and 18.4% of all female respondents
report a conflict with their Masters and PhD advisor(s), respectively,
$p<0.05$. In addition, female respondents were found to have a conflict
significantly more often with their PhD advisor(s) compared to their male
counterparts, $p<0.05$. Considering the primary advisor’s gender, we see that
having a male PhD primary advisor is associated with more conflicts than
having a male Masters primary advisor, $p<0.05$. Otherwise, the primary
advisor’s gender is not found to significantly associate with conflict
prevalence. Regarding the issue of gender concordance (i.e., the primary
advisor and the respondent’s gender alignment), we see that when the genders
do not align, conflicts are more prevalent during the PhD period compared to
the Masters period, $p<0.05$.

Considering the primary advisor’s academic title, we see that having a
Professor as the primary PhD advisor is associated with a significantly higher
conflict prevalence than having a Professor as the primary Masters advisor,
$p<0.05$. Specifically, 16.4% of the respondents who had a Professor as their
primary PhD advisor have reported a conflict compared to 10.2% of those who
had a Professor as their primary Masters advisor. Otherwise, the primary
advisor’s academic title is not found to significantly associate with conflict
prevalence.

As for the age difference between the primary advisor and the advisee, we see
that a 20-40 years difference is associated with a statistically significant
increase in conflict prevalence from the Masters to the PhD period.
Specifically, 19.9% of the relevant respondents have reported a conflict with
thier PhD advisor(s) compared to 9.7% who reported a conflict with their
Masters advisor(s). Otherwise, the age difference is not found to
significantly associate with conflict prevalence.

Considering the number of published papers during the relevant period, we
encounter only a single statistically significant difference. Specifically,
59.2% of the respondents who published two papers during their Masters
reported a conflict with their advisor(s) compared to only 17.3% of the
respondents who published two papers during their PhD significantly more the
relevant training period, $p<0.05$. Otherwise, the number of published papers
is not found to significantly associate with conflict prevalence.

For all six examined continents, the prevalence of conflicts with one’s PhD
advisor(s) is higher compared to that with Masters advisor(s). However, the
difference is only statistically significant for Europe (15.4% vs 9.3%,
$p<0.05$), whereas the difference in North America (14% vs 5.8%), South
America (35.9% vs 10.3$), Africa (29.3% vs 19.5%) and Asia (12.6% vs 11.3%) is
not statistically significant.

Characteristic |  |  Masters |  PhD |  p value
---|---|---|---|---
Number of Advisors |  Single (562, 476) |  8.7% (49) |  17.6% (75) |  $0.003$
Multiple (114, 200) |  19.6% (22) |  13.8% (28) |  $0.298$
p value |  $0.030$ |  $0.019$ |  -
Advisee’s Discipline |  Exact (246) |  11.0% (27) |  17.1% (42) |  $0.037$
Social (184) |  8.2% (15) |  17.4% (32) |  $0.052$
Nature (88) |  8.0% (7) |  19.3% (17) |  $0.188$
Engineering (108) |  16.7% (18) |  9.3% (10) |  $0.083$
Medicine (50) |  6.0% (3) |  22.0% (11) |  $0.418$
p value |  $0.071$ |  $0.126$ |  -
Advisee’s Gender |  Male (469) |  11.3% (49) |  15.8% (74) |  $0.004$
Female (207) |  8.2% (17) |  18.4% (38) |  $0.026$
p value |  $0.069$ |  $0.040$ |  -
Primary Advisor’s Gender |  Male (580, 617) |  11.5% (67) |  17.0% (105) |  $0.013$
Female (96, 59) |  10.3% (10) |  11.9% (7) |  $0.528$
p value |  $0.403$ |  $0.094$ |  -
Gender Concordance |  Yes (205, 476) |  11.0% (23) |  15.8% (75) |  $0.062$
No (471, 200) |  8.8% (41) |  18.5% (37) |  $0.040$
p value |  $0.138$ |  $0.063$ |  -
Primary Advisor’s Title |  Dr. (471, 35) |  10.7% (50) |  20.0 % (7) |  $0.317$
Prof. (205, 641) |  10.2% (21) |  16.4% (105) |  $0.046$
p value |  $0.309$ |  $0.066$ |  -
Age difference |  Younger (2, 4) |  0% (0) |  0% (0) |  -
$<5$ years (7, 10) |  14.3% (1) |  10.0% (1) |  -
$5-10$ years (52, 34) |  7.7% (4) |  14.7% (5) |  $0.419$
$10-20$ years (306, 176) |  11.1% (34) |  12.5% (22) |  $0.703$
$20-40$ years (247, 412) |  9.7% (24) |  19.9% (82) |  $0.038$
$>40$ years (62, 40) |  11.3% (7) |  5% (2) |  $0.832$
p value |  $0.183$ |  $0.067$ |  -
Papers Published |  $0$ (300, 18) |  10.3% (31) |  5.6% (1) |  -
$1$ (294, 59) |  46.0% (135) |  18.6% (11) |  $0.059$
$2$ (65, 156) |  59.2% (38) |  17.3% (27) |  $0.038$
$3$ (17, 234) |  29.4% (5) |  16.2% (38) |  $0.216$
$4$ (0, 107) |  0% (0) |  15.0% (16) |  -
$5$ (0, 102) |  0% (0) |  18.6% (19) |  -
p value |  $0.012$ |  $0.087$ |  -
Continent |  North America (86) |  5.8% (5) |  14.0% (12) |  $0.063$
South America (39) |  10.3% (4) |  35.9% (14) |  $0.057$
Europe (311) |  9.3% (29) |  15.4% (48) |  $0.040$
Africa (41) |  19.5% (8) |  29.3% (12) |  $0.093$
Asia (151) |  11.3% (17) |  12.6% (19) |  $0.214$
Oceania (49) |  14.6% (7) |  14.6% (7) |  $1.0$
|  p value |  $0.071$ |  $0.055$ |  -
Conflict during Masters |  Yes (70) |  - |  17.2% (12) |  -
No (606) |  - |  11.4% (69) |  -
p value |  - |  $0.031$ |  -
Overall |  |  10.5% (75) |  16.3% (115) |  $0.008$
Table 1: Characteristics of the advisor(s)-advisee relationship and the
associated conflict prevalence ($N$ is given in parentheses).

###  3.3 Peer Conflicts

Here, we consider the respondents’ characteristics and the associated conflict
prevalence as reported in the three relevant questions: 1) Have you ever had a
disagreement with a peer over authorship credit distribution (i.e., who should
get authorship credit or how the author byline should be ordered)? (we denote
this question as Conflict Faced); 2) Have you ever had to demand more
authorship credit on a paper than that was initially assigned to you (i.e.,
get authorship credit or improve your placement in the author byline)?
(denoted as Raised Demands); and 3) Have you ever faced a peer who raised
demands to get more authorship credit than you believed s/he is entitled to
(i.e., get authorship credit or improve his/her placement in the author
byline)? (denoted as Others Demand). Table 2 summarizes the main results.

Starting by considering all respondents together, we see that about one-half
of all respondents have reported facing a conflict over authorship credit
distribution with their peers (i.e., 48.9% reported Yes to Conflict Faced),
demanded to get more authorship credit themselves (i.e., 53.1% reported Yes to
Raised Demands) and encountered peers who demanded to get more credit than
that they are entitled to (i.e., 52.9% reported Yes to Others Demand).

Starting with the issue of gender, Male respondents reported significantly
higher conflict rates in terms of Raised demands (56.1% vs 50.2%) and Others
Demand (48.1% vs 39.6%) but not in Conflict Faced (50.5% vs 54.6%).

Considering respondents’ age, we see that older respondents tend to report
higher conflict rates. Considering Conflict Faced, the conflict prevalence
ranges from 26.8% for the 25-35 age group, to 74.4% for the above 65 age group
with the prevalence rate monotonically increasing by age group, $p<0.01$.
Similarly, for the Raised Demands, the prevalence ranges from 38.4% for the
26-35 age group to 67.4% for the above 65 age group with the prevalence
monotonically increasing by age group, $p<0.05$. Albeit not statistically
significant, a similar pattern is observed for the Others Demand, with the
prevalence generally increasing from 28.3% for the 26-35 age group to 60% for
the 56-65 age group. The slight decrease in conflict prevalence observed for
the above 65 age group (only 53.5%) is presumably partially attributed with
the lack of statistical significance. Similarly, considering the respondents’
academic age, a similar pattern is observed with older respondents generally
reporting higher conflict prevalence. Considering Conflict Faced, the conflict
prevalence ranges from 23.9% for the 3-5 age group to 72.3% for the above 20
age group with the prevalence monotonically increasing by age group, $p<0.05$.
Likewise, considering Raised Demands, the conflict prevalence ranges from
39.1% for the 3-5 age group to 66.5% for the above 20 age group with the
prevalence monotonically increasing by age group, $p<0.05$. Again, albeit not
statistically significant, a similar pattern is observed for the Others Demand
with the prevalence generally increasing from 20.7% for the 3-5 age group to
56.6% for the above 20 age group, $p=0.06$.

Similar to the age-based differences discussed above, the respondents’
academic title is strongly associated with conflict rates as well.
Specifically, Professors report higher conflict prevalence rates compared to
Doctors (Conflict Faced: 71.1% vs 39.1%; Raised Demands: 66.3% vs 46.2%; and
Others demand 58.4% vs 36.9%), all at $p<0.01$.

Considering the respondents’ workload, as represented by the number of
concurrent projects pursued by the respondents, we see that a non-significant
general trend where more concurrent projects are slightly associated with
higher conflict prevalence. However, this trend is not statistically
significant, possibly due to the extremely similar results observed for the
cases of three, four and five+ concurrent projects.

Focusing on the respondents’ publication patterns, we see that the number of
co-authored papers is associated with conflict prevalence across the three
examined questions, $p<0.05$. Specifically, the single co-authored paper group
reported 22.9% (Conflict Faced), 33.3% (Raised Demands) and 12.5% (Others
Demand) compared to 67.8%, 64.4% and 61.9% reported by the 10+ co-authored
group, respectively. This result is naturally aligned with those presented
above considering one’s age, academic age and title. When considering the
number of solo papers, no statistically significant differences are found.

Characteristic |  |  Conflict Faced |  Raised demands |  Others demand
---|---|---|---|---
Gender |  Male (469) |  50.5% (237) |  56.1% (263) |  48.1% (226)
Female (207) |  54.6% (113) |  50.2% (104) |  39.6% (82)
p value |  0.208 |  0.058 |  0.041
Age |  $<25$ (4) |  0% (0) |  0% (0) |  0% (0)
$26-35$ (138) |  26.8% (37) |  38.4% (53) |  28.3% (39)
$36-45$ (216) |  44.4% (96) |  49.5% (107) |  41.7% (90)
$46-55$ (175) |  64.0% (112) |  64.6% (113) |  54.9% (96)
$56-65$ (100) |  73.0% (73) |  65.0% (65) |  60.0% (60)
$>65$ (43) |  74.4% (32) |  67.4% (29) |  53.5% (23)
p value |  0.009 |  0.045 |  0.060
Academic Age |  $1-2$ (17) |  5.9% (1) |  23.5% (4) |  29.4% (5)
$3-5$ (92) |  23.9% (22) |  39.1% (36) |  20.7% (19)
$6-9$ (146) |  40.4% (59) |  47.3% (69) |  33.6% (49)
$10-20$ (179) |  52.0% (93) |  54.2% (97) |  54.7% (98)
$>20$ (242) |  72.3% (175) |  66.5% (161) |  56.6% (137)
p value |  0.014 |  0.030 |  0.062
Title |  Below Dr. (19) |  0% (0) |  21.0% (4) |  15.8% (3)
Dr. (366) |  39.1% (143) |  46.2% (169) |  36.9% (135)
Prof. (291) |  71.1% (207) |  66.3% (193) |  58.4% (170)
p value |  0.001 |  0.004 |  0.004
#Projects |  $1$ (78) |  23.1% (18) |  26.9% (21) |  15.4% (12)
$2$ (203) |  40.9% (83) |  49.8% (201) |  31.0% (63)
$3$ (185) |  61.6% (114) |  60.5% (112) |  55.1% (102)
$4$ (86) |  60.5% (52) |  65.1% (56) |  57.0% (49)
$5+$ (124) |  66.9% (83) |  62.1% (77) |  66.1% (82)
p value |  0.081 |  0.099 |  0.050
#Co-authored papers |  $0$ (21) |  9.5% (2) |  19.0% (4) |  4.8% (1)
$1$ (48) |  22.9% (11) |  33.3% (16) |  12.5% (6)
$2-5$ (127) |  35.4% (45) |  39.4% (50) |  25.2% (32)
$5-9$ (123) |  40.7% (50) |  54.5% (67) |  39.0% (48)
$10+$ (357) |  67.8% (242) |  64.4% (230) |  61.9% (221)
p value |  0.029 |  0.042 |  0.011
#solo papers |  $0$ (185) |  27.6% (51) |  42.2% (78) |  27.0% (50)
$1$ (80) |  36.2% (29) |  50.0% (40) |  35.0% (28)
$2-5$ (133) |  66.2% (88) |  54.9% (73) |  63.9% (85)
$5-9$ (125) |  61.6% (77) |  61.6% (77) |  52.0% (65)
$10+$ (153) |  68.6% (105) |  64.7% (99) |  52.3% (80)
p value |  0.087 |  0.059 |  0.104
Continent |  North America (86) |  51.2% (44) |  58.1% (50) |  47.7% (41)
South America (39) |  66.7% (26) |  53.8% (21) |  51.3% (20)
Europe (311) |  53.4% (166) |  52.4% (163) |  46.0% (143)
Africa (41) |  43.9% (18) |  63.4% (26) |  46.3% (19)
Asia (151) |  49.7% (75) |  51.0% (77) |  43.7% (66)
Oceania (49) |  43.8% (21) |  62.5% (31) |  39.6% (19)
|  p value |  $0.083$ |  $0.075$ |  $0.070$
Overall |  |  48.9% (368) |  53.1% (399) |  52.9% (398)
Table 2: Characteristics of the respondent and the associated conflict
prevalence ($N$ is given in parentheses).

Turning to the connection between the three questions of interest, as can be
seen in Table 3, the three seem to be highly interwoven. Specifically,
providing a positive answer to any one of the three questions is strongly
associated with increased chances of providing positive answers to the
remaining two questions, $p<0.05$. For example, those who reported Conflict
Faced are significantly more likely to report Raised Demands (65.7% vs 42%)
and Others Demand (60.9% vs 29.1%). Similarly, those who reported Raised
Demands are significantly more likely to report Others Demand (57.5% vs 31.4%)
and vice-versa (68.5% vs 43.4%).

|  |  Conflict faced |  Raised demands |  Others demand
---|---|---|---|---
Conflict faced |  Yes (350) |  |  65.7% (230) |  60.9% (213)
No (326) |  |  42.0% (137) |  29.1% (95)
p value |  |  $0.038$ |  $0.025$
Raised demands |  Yes (367) |  62.7% (230) |  |  57.5% (211)
No (309) |  38.8% (120) |  |  31.4% (97)
p value |  $0.018$ |  |  $0.016$
Others demand |  Yes (308) |  69.2% (213) |  68.5% (211) |
No (368) |  37.2% (137) |  42.4% (155) |
p value |  $0.033$ |  $0.026$ |
Table 3: Conflict prevalence across the three examined questions ($N$ is given
in parentheses).

###  3.4 Cross Analysis

Last, we examine the possible link between authorship credit conflicts with
one’s Masters and/or PhD advisor(s) and his/her subsequent conflicts with
his/her peers after graduation. As can be seen in Table 4, having a conflict
with one’s advisor(s) (either Masters and/or PhD) is associated with an
increased rate of peer conflicts, all at $p<0.05$. Specifically, those who
reported a conflict with at least one of their advsiors are significantly more
likely to provide a positive answer to Conflict Faced (59% vs 49.4%), Raised
Demands (59% vs 52.7%) and Others Demand (51.8% vs 43.5%). When breaking down
the conflicts to conflicts with one’s Masters and PhD advisor(s), we see that
the PhD conflicts follow the same pattern, and present a statistically
significant association with one’s subsequent peer conflicts. Specifically, a
conflict with one’s PhD advisor is associated with higher Conflict Faced
(62.5% vs 49.6%), Raised Demands (59.8% vs 53.2%) and Others Demand (55.4% vs
43.6%). However, a conflict with one’s Masters advisor(s), follows the same
pattern only for Others Demand (51.4% vs 44.9%). While the difference in
Raised demands is statistically indistinguishable, for Conflict Faced we see
the opposite trend, where those who reported a conflict with their Masters
advisor(s) reporting less peer conflicts (48.6% vs 52.1%).

Past conflict |  |  Conflict Faced |  Raised demands |  Others demand
---|---|---|---|---
Masters |  No (606) |  52.1% (316) |  54.1% (328) |  44.9% (272)
Yes (70) |  48.6% (34) |  55.7% (39) |  51.4% (36)
p value |  $0.046$ |  $0.071$ |  $0.008$
PhD |  No (564) |  49.6% (280) |  53.2% (300) |  43.6% (246)
Yes (112) |  62.5% (70) |  59.8% (67) |  55.4% (62)
p value |  $0.006$ |  $0.028$ |  $0.009$
Any |  No (510) |  49.4% (252) |  52.7% (269) |  43.5% (222)
Yes (166) |  59.0% (98) |  59.0% (98) |  51.8% (86)
p value |  $0.002$ |  $0.027$ |  $0.040$
Table 4: Characteristics of the respondent and the associated conflict
prevalence ($N$ is given in parentheses).

##  4 Discussion and Conclusions

Our results combine to suggest a complex, arguably disturbing, multifaceted
picture.

First, our results show that conflicts over authorship credit distribution are
often encountered very early in one’s academic career. Specifically, nearly
one out of four participants have reported at least one conflict with an
advisor either during their Masters and/or their PhD (24.5%). These conflicts
are especially prominent during one’s PhD training period, a period which is
naturally longer, mostly more productive, and possibly more competitive than
the Masters training one. Interestingly, those who had a conflict with their
Masters advisor(s) are less likely to have a conflict with their PhD
advisor(s). A reasonable explanation could pose that the advisees who
encountered a conflict with their Masters advisor(s) have chosen a different
advisor(s) when pursuing their PhD. Conflict prevalence with one’s advisor(s)
seems to be high despite some non-consistent moderators such as the number of
advisors, discipline, genders, titles, productivity, and geography.

Authorship credit distribution conflicts seem to intensify later on in one’s
career, this time in the form of peer conflicts. Specifically, the results
suggest that roughly one-half of the participants in this study have
experienced a conflict with their peers. These conflicts seem to escalate with
age and experience with older, more experienced, and more productive
participants reporting higher conflict rates compared to their counterparts.
Conflict prevalence with one’s peers seems to be high despite some non-
consistent moderators such as gender, workload, and geography.

Interestingly, those who had a conflict with an advisor during their training,
either with their Masters advisor(s) and/or their PhD advisor(s), are more
likely to encounter conflicts later on in their academic careers with their
peers. We believe that this intriguing phenomenon can be explained in two,
possibly complementary, ways. First, it may be the case that both types of
conflicts are a consequence of one’s personality and behavioral traits. For
example, some scholars may be self-centered, egotistical, or even
narcissistic, factors which are naturally associated with a more conflict-
prone demeanor [54, 55, 56]. Alternatively, conflict-prone advisors may have
passed on certain academic norms, beliefs, and values to their advisees,
causing them to follow a conflict-prone path, similar to how parental
influences shape the development and choices of children later on in their
lives [57, 58]. For example, an advisee may have unwittingly adopted some
contentious behaviors by modeling or mimicking a past advisor, behaviors which
have led to the very conflict they had with that advisor. Given the great
benefits and importance of mentoring in academia [59, 60, 61], a more in-depth
investigation into this issue seems merited.

Taken jointly, our results strongly suggest a systematic challenge in academia
rather than a small, confined phenomenon that could be attributed to a few bad
apples. Specifically, the consistency of the results across countries, fields
of research, and most examined socio-demographic properties suggest that the
issue is of a very large scale and should be treated as such. In addition, the
fact that conflict-prone advisees evolve into conflict-prone scholars raises
concerns about the current academic advisement practices.

In future work, we intend to investigate additional academic conflicts which
may arise in other interactions academics have. For example, a scholar may act
as a reviewer or committee member for a grant proposal or a submitted paper
for consideration. In these settings, that scholar may be tempted to leverage
his/her role and act in a self-interested way by providing a negative review
for a competing proposal or requesting additional references to specific works
s/he authored in the past. Unfolding the unique dynamics in such settings can
help establish a more complete understanding of potential conflicts in
academia and can be instrumental in developing new policies to mitigate such
potential conflicts. Finally, as this study is based on the self-reported past
experiences of the participants, future work can also focus on tracking
conflicts as they occur and evolve over time and consider them case-by-case in
a qualitative manner.

## References

  * [1] Sooho Lee and Barry Bozeman  “The impact of research collaboration on scientific productivity”  In _Social studies of science_ 35.5 Sage Publications Sage CA: Thousand Oaks, CA, 2005, pp. 673–702
  * [2] Mott Greene  “The demise of the lone author”  In _Nature_ 450.7173 Nature Publishing Group, 2007, pp. 1165–1165
  * [3] Jonathan Adams  “The fourth age of research”  In _Nature_ 497.7451 Nature Publishing Group, 2013, pp. 557–560
  * [4] Stefan Wuchty, Benjamin F Jones and Brian Uzzi  “The increasing dominance of teams in production of knowledge”  In _Science_ 316.5827 American Association for the Advancement of Science, 2007, pp. 1036–1039
  * [5] R.. Slone  “Coauthors’ Contributions to Major Papers Published in the AJR: Frequency of Undeserved Coauthorship”  In _AJR_ , 1996
  * [6] J. Wang, R. Hooi, A.. Li and M-H. Chou  “Collaboration patterns of mobile academics: The impact of international mobility”  In _Science and Public Policy_ 46.3, 2019, pp. 450–462
  * [7] T. Lazebnik, S. Back and L. Shami  “Academic Co-authorship is a Risky Game”  In _arXiv_ , 2022
  * [8] M. Schymura and A. Löschel  “Investigating JEEM Empirically: A Story of Co-Authorship and Collaboration”  In _ZEW - Centre for European Economic Research Discussion_ , 2012, pp. 12–029
  * [9] Z. Barta  “Publication games: In the web of reciprocity”  In _PLOS ONE_ 17.10, 2022, pp. 1–14
  * [10] K. Urbanska, S. Huet and S. Guimond  “Does increased interdisciplinary contact among hard and social scientists help or hinder interdisciplinary research?”  In _PLOS ONE_ 14.9, 2019, pp. e0221907
  * [11] Wesley Shrum, Ivan Chompalov and Joel Genuth  “Trust, conflict and performance in scientific collaborations”  In _Social studies of science_ 31.5 Sage Publications London, 2001, pp. 681–730
  * [12] Barry Bozeman and Elizabeth Corley  “Scientists’ collaboration strategies: implications for scientific and technical human capital”  In _Research policy_ 33.4 Elsevier, 2004, pp. 599–616
  * [13] B Bozeman, J Youtie, CP Slade and M Gaughan  “The “dark side” of academic research collaborations: Case studies in exploitation, bullying and unethical behavior”  In _annual meeting of the Society for Social Studies of Science (4S) October_ 1720, 2012, pp. 2012
  * [14] M. Urassa et al.  “Cross-cultural research must prioritize equitable collaboration”  In _Nature Human Behaviour_ 5, 2021, pp. 668–671
  * [15] P. Borry, P. Schotsmans and K. Dierickx  “Author, contributor or just a signer? A quantitative analysis of authorship trends in the field of bioethics”  In _Bioethics_ 20.4 Wiley Online Library, 2006, pp. 213–220
  * [16] S. Fiialka  “Co-authorship in the context of academic integrity”  In _Current Issues of Mass Communication_ 26, 2019, pp. 54–68
  * [17] F. Mansoor and K. Ameen  “Promoting Academic Integrity in South Asian Research Culture: The Case of Pakistani Academic Institutions”  In _South Asian Studies_ 31.2, 2016
  * [18] A.. Gasparyan, L. Ayvazyan and G.. Kitas  “Authorship problems in scholarly journals: considerations for authors, peer reviewers and editors”  In _Rheumatology International_ 33, 2013, pp. 277–284
  * [19] P. Borry, P. Schotsmans and K. Dierickx  “Author, contributor or just a signer? a quantitative analysis of authorship trends in the field of bioethics”  In _Bioethics_ 20.4, 2006, pp. 213–220
  * [20] V.. Gureev, N.. Mazov and I.. Lakizo  “Authorship criteria and the problem of its attribution in scholarly papers”  In _Scientific and Technical Libraries_ 12, 2019, pp. 5–24
  * [21] F. Hesselmann, C. Schendzielorz and N. Sorgatz  “Say my name, say my name: Academic authorship conventions between editorial policies and disciplinary practices”  In _Research Evaluation_ 30.3, 2021, pp. 382–392
  * [22] S.. Mentzelopoulos and S.. Zakynthinos  “Research Integrity, Academic Promotion, and Attribution of Authorship and Nonauthor Contributions”  In _JAMA_ 318.13, 2017, pp. 1221–1222
  * [23] V. Ilik et al.  “OpenVIVO: Transparency in Scholarship”  In _Frontiers in Research Metrics and Analytics_ 2, 2018
  * [24] N.. Vasilevsky et al.  “Is authorship sufficient for today’s collaborative research? A call for contributor roles”  In _Accountability in Research_ 28.1, 2021, pp. 23–43
  * [25] A.. Holcombe, M. Kovacs, F. Aust and B. Aczel  “Documenting contributions to scholarly articles using CRediT and tenzing”  In _PLOS ONE_ 15.12, 2021, pp. 1–11
  * [26] J.A. Teixeira da Silva  “Multiple co-first authors, co-corresponding authors and co-supervisors: a synthesis of shared authorship credit”  In _Online Information Review_ 45.6, 2021, pp. 1116–1139
  * [27] E.. Fong and A.. Wilhite  “Authorship and citation manipulation in academic research”  In _PLOS ONE_ 12.12 Public Library of Science, 2017, pp. 1–34
  * [28] R.. Kornhaber, L.. McLean and R.. Baber  “Ongoing ethical issues concerning authorship in biomedical journals: an integrative review”  In _International Journal of Nanomedicine_ 10, 2015, pp. 4837–4846
  * [29] J… Silva  “How to shape academic freedom in the digital age? Are the retractions of opinionated papers a prelude to “cancel culture” in academia?”  In _Current Research in Behavioral Sciences_ 2, 2021, pp. 100035
  * [30] S.. Lee and C.. Deale  “A matter of degrees: exploring dimensions in the Ph.D. student–advisor relationship in hospitality and tourism education”  In _Journal of Teaching in Travel & Tourism_ 4, 2016, pp. 316–330
  * [31] J. Gómez-Ferria, G. González-Alcaideb and R. LLopis-Goig  “Measuring dissatisfaction with coauthorship: An empirical approach based on the researchers’ perception”  In _Journal of Informetrics_ 13.4, 2019, pp. 100980
  * [32] J.. Mecca et al.  “Researcher Perspectives on Conflicts of Interest: A Qualitative Analysis of Views from Academia”  In _Science and Engineering Ethics_ 21, 2015, pp. 843–855
  * [33] D.. Brunsma, D.. Embrick and J.. Shin  “Graduate Students of Color: Race, Racism, and Mentoring in the White Waters of Academia”  In _Sociology of Race and Ethnicity_ 3.1, 2016
  * [34] J.. Seeman and M.. House  “Authorship Issues and Conflict in the U.S. Academic Chemical Community”  In _Accountability in Research_ 22, 2015, pp. 346–383
  * [35] J-P. Stein and M. Appel  “How to deal with researcher harassment in the social sciences”  In _Nature Reviews Psychology_ 5, 2021, pp. 178–180
  * [36] M.. O’Fallon and K.. Butterfield  “The Influence of Unethical Peer Behavior on Observers’ Unethical Behavior: A Social Cognitive Perspective”  In _Journal of Business Ethics_ 109, 2012, pp. 117–131
  * [37] K. Bakhtiyari et al.  “Ethical and Unethical Methods of Plagiarism Prevention in Academic Writing”  In _International Education Studies_ 7.7, 2014, pp. 52–62
  * [38] C.. Bailey  “Psychopathy, Academic Accountants’ Attitudes toward Unethical Research Practices, and Publication Success”  In _The Accounting Review_ 90.4, 2015, pp. 1307–1332
  * [39] B. Macfarlane, J. Zhang and A. Pun  “Academic integrity: a review of the literature”  In _Studies in Higher Education_ 39.2, 2014, pp. 339–358
  * [40] S.. Boyle, S.. Cotton, P.. Myint and G.. Hold  “The influence of early research experience in medical school on the decision to intercalate and future career in clinical academia: a questionnaire study”  In _BMC Medical Education_ 17, 2017, pp. 245
  * [41] E.. O’Laughlin and L.. BischoffView  “Balancing Parenthood and Academia: Work/Family Stress as Influenced by Gender and Tenure Status”  In _Journal of Family Issues_ 26.1, 2017
  * [42] S. Crabb and S. Ekberg  “Retaining female postgraduates in academia: the role of gender and prospective parenthood”  In _Higher Education Research & Development_ 33.6, 2014, pp. 1099–1112
  * [43] J. Julien, R. Lang, T.. Brown and al.  “Minority Underrepresentation in Academia: Factors Impacting Careers of Surgery Residents”  In _Journal of Racial and Ethnic Health Disparities_ 1, 2014, pp. 238–246
  * [44] I. Skakni, C. Maggiorib, J. Masdonatic and J. Akkermansd  “Ready for careers within and beyond academia? Assessing career competencies amongst junior researchers”  In _Higher Education Research & Development_, 2022
  * [45] A. Grafström and L. Schelin  “How to Select Representative Samples”  In _Scandinavian Journal of Statistics_ 41.2, 2014, pp. 277–290
  * [46] M.. Gallagher, S.. Lopez and S.. Pressman  “Optimism Is Universal: Exploring the Presence and Benefits of Optimism in a Representative Sample of the World”  In _Journal of Personality_ 81.5, 2013, pp. 429–440
  * [47] A. Omair  “Sample size estimation and sampling techniques for selecting a representative sample”  In _Journal of Health Specialties_ 2.4, 2014, pp. 142–147
  * [48] B. Rosner  “Fundamentals of Biostatistics (7th Edition)”  In _Brooks/Cole_ , 2010
  * [49] D. Erocal  “UNESCO Science Report Towards 2030”  In _United Nations Educational,Scientific and Cultural Organization_ , 2015
  * [50] V.. Berger and Y. Zhou  “Kolmogorov–Smirnov Test: Overview”  In _Wiley StatsRef: Statistics Reference Online_ , 2014
  * [51] K. Pearson  “X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling”  In _The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science_ 50.302 Informa UK Limited, 1900, pp. 157–175
  * [52] W. Haynes  “Bonferroni Correction”  In _Encyclopedia of Systems Biology_ , 2013, pp. 154–154
  * [53] K.. Srinath  “Python – The Fastest Growing Programming Language”  In _International Research Journal of Engineering and Technology_ 4.12, 2017
  * [54] R.. Friedman, S.. Tidd, S.. Currall and J.. Tsai  “What Goes Around Comes Around: The Impact of Personal Conflict Style On Work Conflict and Stress”  In _International Journal of Conflict Management_ 11.1, 2000, pp. 32–55
  * [55] J.. Bono, T.. Boles, T.. Judge and K.. Lauver  “The Role of Personality in Task and Relationship Conflict”  In _Journal of Personality_ 70, 2002, pp. 311–344
  * [56] N. Ayub, S.. AlQurashi, W.. Al-Yafi and K. Jehn  “Personality traits and conflict management styles in predicting job performance and conflict”  In _International Journal of Conflict Management_ 28.5, 2017, pp. 671–694
  * [57] J.. Cooper, R.. Kidwell and K.. Eddleston  “Boss and Parent, Employee and Child: Work-Family Roles and Deviant Behavior in the Family Firm”  In _Fam Relat_ 62, 2013, pp. 457–471
  * [58] J. Grote  “Conflicting Generations: A New Theory of Family Business Rivalry”  In _Family Business Review_ 16.2, 2003, pp. 113–124
  * [59] Mengjiao Qi et al.  “Standing on the shoulders of giants: the effect of outstanding scientists on young collaborators’ careers”  In _Scientometrics_ 111.3 Springer, 2017, pp. 1839–1850
  * [60] Jean F Liénard, Titipat Achakulvisut, Daniel E Acuna and Stephen V David  “Intellectual synthesis in mentorship determines success in academic careers”  In _Nature communications_ 9.1 Nature Publishing Group, 2018, pp. 1–13
  * [61] Ariel Rosenfeld and Oleg Maksimov  “Should young computer scientists stop collaborating with their doctoral advisors?”  In _Communications of the ACM_ 65.10, 2022, pp. 66–72
  * [62] J. Hae-Ok and Y. Eun-Yi  “The Influence of Gender Role Conflicts, Academic Stress Coping Ability, and Social Support on Adaptations to College Life among Male Nursing Students”  In _The Journal of the Korea Contents Association_ 14.12, 2014, pp. 796–807
  * [63] S.. Vitell, E.. Dickerson and T.. Festervand  “Ethical Problems, Conflicts and Beliefs of Small Business Professionals”  In _Journal of Business Ethics_ 28, 2000, pp. 15–24
  * [64] R. Misra and L.. Castillo  “Academic Stress Among College Students: Comparison of American and International Students”  In _International Journal of Stress Management_ 11.2, 2004, pp. 132–148
  * [65] C.. Seiger and B.. Wiese  “Social support from work and family domains as an antecedent or moderator of work–family conflicts?”  In _Journal of Vocational Behavior_ 75.1, 2009, pp. 26–37
  * [66] T. Basáñez et al.  “Measuring Acculturation Gap Conflicts Among Hispanics: Implications for Psychosocial and Academic Adjustment”  In _Journal of Family Issues_ 35.13, 2013
  * [67] M. Rahman et al.  “Work to family, family to work conflicts and work family balance as predictors of job satisfaction of Malaysian academic community”  In _Journal of Enterprising Communities: People and Places in the Global Economy_ , 2020
  * [68] S.. Wami, M. Eremie and K.. Wami  “Marital Conflicts on Academic Performance of Secondary School Students in Port Harcourt Metropolis, Rivers State”  In _International Journal of Innovative Psychology & Social Development_ 9.1, 2021, pp. 74–83
  * [69] S.. Bruton, D.. Sacco and R. Didlake  “Financial Conflicts of Interest, Disclosure, and Academic Discipline”  In _Journal of Empirical Research on Human Research Ethics_ 11.2, 2016
  * [70] A. Grund, B.. Nina and S. Fries  “Torn between study and leisure: How motivational conflicts relate to students’ academic and social adaptation”  In _Journal of Educational Psychology_ 106.1, 2014, pp. 242–257
  * [71] S. Kumar and K. Ratnavelu  “Perceptions of Scholars in the Field of Economics on Co-Authorship Associations: Evidence from an International Survey”  In _PLOS ONE_ 11.6, 2016, pp. e0157633
  * [72] G. Helgesson et al.  “Misuse of Coauthorship in Medical Theses in Sweden”  In _Journal of Empirical Research on Human Research Ethics_ 13.4, 2018
  * [73] M.. Meyer and D. McMahon  “An Examination of Ethical Research Conduct by Experienced and Novice Accounting Academics”  In _Issues in Accounting Education_ 19.4, 2004, pp. 413–442
  * [74] J. O’Brien et al.  “Honorary Coauthorship: Does It Matter?”  In _Canadian Association of Radiologists Journal_ 60.5, 2009, pp. 231–236
  * [75] H.. Ahmed, A. Hadi and N. Choudhury  “Authorship conflict in Bangladesh: an exploratory study?”  In _Learned Publishing_ 23.10, 2010, pp. 319–325
  * [76] J.. Reinisch, W-Y. Li, D. Yu and J. Walker  “Authorship Conflicts: A Study of Awareness of Authorship Criteria among Academic Plastic Surgeons”  In _Plastic and Reconstructive Surgery_ 132.2, 2010, pp. 303e–310e

## Appendix

### Questionnaire

In this section, we provide the questionnaire’s questions and possible
answers:

  * •

Gender: Male, Female, Prefer not to say.

  * •

Age: 18-25, 26-35, 36-45, 46-55, 56-65, 66+

  * •

Academic degree: First, Second, Third, Professor

  * •

Main field of research: Informatics, Computer Science (CS), Environmental
science, Social sciences, Philosophy, Literature, Linguistics, History, Law,
Politics, Economics, Management, Sociology, Psychology, Nano/Micro science,
Applied physics, Mathematics, Physics, Chemistry, Mechanical engineering,
Electrical and electronic engineering, Civil engineering, Architecture and
building engineering, Material engineering, Process/Chemical engineering,
Neuroscience, Oncology, Genome science, Biological Science, Basic biology,
Anthropology, Animal life science, Pharmacy, Basic medicine, Boundary
medicine, Society medicine, Clinical internal medicine, Clinical surgery,
Dentistry, Nursing.

  * •

How many years have passed since your first academic publication (i.e., what
is your academic age): 0, 1-2, 3-5, 6-9, 10-20, 20+.

  * •

Country of primary affiliation: a list of 196 countries from
https://gist.github.com/kalinchernev/486393efcca01623b18d.

  * •

Based on the last 5 years, on average, how many research projects do pursue
concurrently?: 1, 2, 3, 4, 5+.

  * •

How many academic papers have you published thus far with one or more co-
author(s) other than your advisor(s)?: 0, 1, 2-5, 6-10, 10+.

  * •

How many academic papers have you published with no co-authors (i.e., solo
papers)?: 0, 1, 2-5, 6-10, 10+.

  * •

How many advisors did you have during your Masters training period?: 1, 2,
More than 2, I don’t have a Masters.

  * •

How many papers did you publish during your Masters with your advisor(s)?: 0,
1, 2, 3+.

  * •

How many advisors did you have during your Ph.D. training period?: 1, 2, 3, 4,
5.

  * •

How many papers did you publish during your Ph.D. studies with your
advisor(s)?: 1, 2, 3, 4, 5+.

  * •

How many years your primary Masters advisor is older than you?: Younger than
me, 0-5, 5-10, 10-20, 20-40, 40+.

  * •

What was your primary Masters advisor’s academic title?: Dr, Prof.

  * •

What was your primary Masters advisor’s gender?: Male, Female.

  * •

Have you ever had a disagreement with your Masters’ advisor(s) over authorship
credit distribution (i.e., who should get authorship credit or how the author
byline should be ordered) ?: Yes, No.

  * •

How many years your primary Ph.D.’s (or MD) advisor was older than you?:
Younger than me, 0-5, 5-10, 10-20, 20-40, 40+.

  * •

What was your primary Ph.D. (or MD) advisor’s gender?: Male, Female.

  * •

Have you ever had a disagreement with your PhD’s (or MD) advisor(s) over
authorship credit distribution (i.e., who should get authorship credit or how
the author byline should be ordered) ?: Yes, No.

  * •

What was your Ph.D.’s (or MD) primary advisor’s academic title?: Yes, No.

  * •

Have you ever had a disagreement with a peer over authorship credit
distribution (i.e., who should get authorship credit or how the author byline
should be ordered) ?: Yes, No.

  * •

Have you ever had to demand more authorship credit on a paper than that was
initially assigned to you (i.e., get authorship credit or improve your
placement in the author byline) ?: Yes, No.

  * •

Have you ever faced a peer who raised demands to get more authorship credit
than you believed s/he is entitled to (i.e., get authorship credit or improve
his/her placement in the author byline) ?: Yes, No.

### Cohort size comparison dataset

Table 5 summarizes 22 studies about social and political practices in academia
that are based on questionnaires.

Title |  Group invited size |  Group participant size |  Source
---|---|---|---
Balancing Parenthood and Academia: Work/Family Stress as Influenced by Gender and Tenure Status |  264 |  264 |  [40]
Retaining female postgraduates in academia: the role of gender and prospective parenthood |  249 |  249 |  [41]
Minority Under representation in Academia: Factors Impacting Careers of Surgery Residents |  3726 |  1217 |  [42]
Ready for careers within and beyond academia? Assessing career competencies amongst junior researchers |  727 |  727 |  [43]
The Influence of Gender Role Conflicts & Academic Stress Coping Ability, and Social Support on Adaptations to College Life among Male Nursing Students |  225 |  225 |  [44]
Ethical Problems, Conflicts and Beliefs of Small Business Professionals |  1300 |  135 |  [62]
Academic Stress Among College Students: Comparison of American and International Students. |  392 |  392 |  [63]
Social support from work and family domains as an antecedent or moderator of work–family conflicts? |  107 |  107 |  [64]
Measuring Acculturation Gap Conflicts Among Hispanics: Implications for Psychosocial and Academic Adjustment |  283 |  283 |  [65]
Work to family, family to work conflicts and work family balance as predictors of job satisfaction of Malaysian academic community |  280 |  280 |  [66]
Marital Conflicts on Academic Performance of Secondary School Students in Port Harcourt Metropolis, Rivers State |  1951 |  195 |  [67]
Financial Conflicts of Interest, Disclosure, and Academic Discipline |  10 |  10 |  [68]
Torn between study and leisure: How motivational conflicts relate to students’ academic and social adaptation |  733 |  733 |  [69]
Perceptions of Scholars in the Field of Economics on Co-Authorship Associations: Evidence from an International Survey |  580 |  580 |  [70]
Misuse of Coauthorship in Medical Theses in Sweden |  285 |  285 |  [71]
Measuring dissatisfaction with coauthorship: An empirical approach based on the researchers’ perception |  2344 |  2344 |  [72]
Coauthors’ Contributions to Major Papers Published in the AjR |  272 |  196 |  [31]
An Examination of Ethical Research Conduct by Experienced and Novice Accounting Academics |  176 |  176 |  [5]
Honorary Coauthorship: Does It Matter? |  195 |  127 |  [73]
Authorship conflict in Bangladesh: an exploratory study |  100 |  100 |  [74]
The influence of early research experience in medical school on the decision to intercalate and future career in clinical academia: a questionnaire study |  117 |  66 |  [75]
A Study of Awareness of Authorship Criteria among Academic Plastic Surgeons |  916 |  744 |  [76]
Mean $\pm$ standard deviation |  $692\pm 908$ |  $429\pm 518$ |
Table 5: Questionnaire-based paper about academia with their cohort sizes.


# On the Superiority of the University of Arizona’s Physics Club

E. Jesina  Physics Club, Department of Physics, University of Arizona, Tucson,
AZ, 85721  M. Harrison  Physics Club, Department of Physics, University of
Arizona, Tucson, AZ, 85721  H. Andras-Letanovszky  Physics Club, Department of
Physics, University of Arizona, Tucson, AZ, 85721  D. Krug  Physics Club,
Department of Physics, University of Arizona, Tucson, AZ, 85721  A. Golinkin
Physics Club, Department of Physics, University of Arizona, Tucson, AZ, 85721
B. Kohn  Physics Club, Department of Physics, University of Arizona, Tucson,
AZ, 85721  T. Brown  Physics Club, Department of Physics, University of
Arizona, Tucson, AZ, 85721  A. Rose  Physics Club, Department of Physics,
University of Arizona, Tucson, AZ, 85721  P. Chiploonkar  Physics Club,
Department of Physics, University of Arizona, Tucson, AZ, 85721

###### Abstract

We present an analysis on Physics Club’s supremacy over the Astronomy Club at
the University of Arizona. Through a thorough investigation of each club’s
history and content, and subsequent diligent calculations, we have proven
without a doubt that the Physics Club is superior to Astronomy Club.

Humor, Irrelevance, Irreverence, Fire, Physics, Astronomy, Superiority, Jokes,
Pranks: April Fool’s

††software:  LaTeX, Python, PGF/TikZ, Microsoft Paint, Microsoft Excel.

##  1 Introduction

The University of Arizona hosts two astrophysics-related clubs: the Astronomy
Club and the Physics Club, both of which have seen extreme success in the
years following the COVID-19 pandemic. However, a breakdown of the respective
clubs’ statistics finds a significant difference in quality between them, with
Astronomy Club’s quality being noticeably lower than Physics Club’s. From our
research into these statistics, we claim without a doubt that Physics Club is
overall superior to the Astronomy Club.

We further base our accusations on previous work by Barnes et al. (2002) which
discusses the shortcomings of Steward Observatory, the department that houses
the Astronomy Club. We follow this paper as a guideline, as well as Charfman
et al. (2002), for our approach to definitively establishing Physics Club’s
superiority.

##  2 Data

###  2.1 Resignations

Over the past few years, the officer retention of Astronomy Club has been
somewhat lacking. Astronomy Club has had 3 total officer resignations in the
period of 2021 - 2024, whereas in the same period of time, Physics Club has
had $0.5\pm 0.5$ officer resignations. This means the rate of officer
resignations per year is roughly 0.75 for Astronomy Club and only 0.125 for
Physics Club.

This shockingly high rate of resignations in Astronomy Club left the authors
perplexed, as even they didn’t think Astronomy Club was that bad. However,
after extensive and rigorous scientific inquiry, 111Funded by Red Bull GmbH we
have determined that the officer resignation rate of Astronomy Club
$\frac{dR}{dt}$ is governed by the following equation:

$\frac{dR}{dt}=f_{baby}\frac{\omega e^{N_{Kool-Aid}}}{T}$

where $f_{baby}$ is the percentage of club members that are pimply freshmen,
$N_{Kool-Aid}$ is the amount of cults formed at star parties, $\omega$ is the
lameness of presentations at meetings, and $T$ is the amount of time the
officers don’t spend engaged in pointless drama. $f_{baby}$ has been observed
to increase over time, while $T$ has been decreasing rapidly over the past few
years, so we predict $\frac{dR}{dt}$ to increase by several orders of
magnitude over the next decade. Even making the edge-case assumption that all
members are willing and able to be officers, with their average attendance of
45-65 members per meeting, this officer turnover rate would quickly become
unsustainable for Astronomy Club. This clearly demonstrates Physics Club’s
much greater potential for longevity over Astronomy Club.

###  2.2 Succession

Figure 1: Flowchart of the Line of Succession

The Physics Club’s succession plan (UA Physics Club, 2022) is a testament to
the club’s preparedness, reflecting the precision and complexity of its daily
operations. While the Astronomy Club’s approach to officer succession might be
likened to navigating the stars without a telescope—relying on the hope that a
simple special election will fill the void—the Physics Club has charted every
possible eventuality and more (refer to Figure 1). Should the well-ordered
cascade of leadership in cases of unexpected vacancies fail, provisions exist
to secure Senator Bernie Sanders’ (un)willing intervention.

Moreover, the line of succession highlights the Physics Club’s spirit of
generosity and cooperation. In the event of an unprecedented total leadership
vacuum, the club’s benevolence extends beyond the realm of academia, ensuring
any remaining funds are bequeathed to the Community Food Bank of Southern
Arizona—a noble act of community service rarely seen in clubs like the
Astronomy Club, which often lack such foresight. The Physics Club even extends
an olive branch to its Astronomy Club counterparts, allowing for an Astronomy
officer (who is also a Physics Club member) to take the helm, should the need
arise. This gesture of cross-club solidarity, however, appears to be a one-way
street, as no such reciprocity is found in the Astronomy Club’s statutes (UA
Astronomy Club, 2023).

###  2.3 Memes

It has been known since time immemorial that the quality and quantity of memes
held within the Astronomy Club’s slides have been below that of the Physics
Club, but there have been no attempts to compare these memes until now. To go
about our quantitative comparison, we went through the past year’s worth of
available Astronomy and Physics Club slides, tallying the total amount of
memes in both.

Figure 2: Number of Memes per Meeting for both Astronomy Club and Physics Club
and Average Number of Memes for both Astronomy Club and Physics Club. While
there have certainly been occasions where the Astronomy Club memes per meeting
have surpassed the Physics Club average, this is a rarity and should be
discounted as an anomaly.

We counted a total of 209 memes for Astronomy Club during the period between
the 25th of August 2023 and the 29nd of March 2024, having a total of 23
meetings during that time, with an average of $9.087$ memes per meeting. In
comparison, during that same period, we counted 315 memes for Physics Club
while having only 18 meetings, with an average of $17.5$ memes per meeting,
almost twice the number of average Astronomy Club memes (see Figure 2). Thus,
the sheer domination the Physics Club has over the Astronomy Club when it
comes to the quantity of memes was clearly obvious to the authors.

###  2.4 Demos

Physics Club has a known affinity for demonstrations (lovingly referred to as
”demos”), which has led to merry destruction on many occasions. Most notable
is the Pumpkin Smashing, an annual tradition where pumpkins are frozen in
liquid nitrogen and then flung from high places, such as ladders. Another
common phenomenon is fire demos, where Physics Club members light objects on
fire in an increasingly entertaining number of ways, including rockets, arson,
melting coins, and glassblowing. As mentioned previously, the club makes
frequent use of liquid nitrogen, which has been used to make ice cream,
shatter assorted fruits and vegetables, and even make superconductors.

It is obvious that Physics Club has great success with attracting attention
with demos. However, in astronomy, most celestial objects are very far away.
This makes it hard to do demos. The one thing Astronomy Club does do is
something called ”stargazing”, an archaic act where they look at objects very
far away that have absolutely no effect on anybody on Earth. This is very
boring, as these objects cannot be lit on fire or doused in liquid nitrogen,
meaning that there is no point to this ”stargazing”. Physics Club is able to
do many demos, and this makes us even cooler than liquid nitrogen (see Figure
3) and hotter than fire. This lack of allure is why Astronomy Club cannot
attract new members or impress their current ones.

Figure 3: Total increase in coolness of Physics Club and total number of demos
over the 2023-2024 school year. There is a clear direct correlation of the
amount of liquid nitrogen spilled on the floor of PAS 201 and the overall
coolness of Physics Club’s members.

###  2.5 Professor Talks

The superiority of Physics Club can also be seen through the amount of Notable
Interdisciplinary Profound Professorial Lectures Exemplifying Science
(NIPPLES) it has held. In the past 63,113,472 seconds alone, Physics Club has
had 14 NIPPLES, whereas Astronomy Club’s NIPPLES count lies at a measly $1\pm
0.2$. The discrepancy in these values suggests that the members of Physics
Club are much more learned than those of Astronomy Club.

Another thing of note in the NIPPLES of Physics Club is the vast swaths of
fields that these lectures have touched upon. Some notable NIPPLES have
integrated physics with global warming, computer science, and biology. The
singular NIPPLES topic of Astronomy Club in the past 63,113,472 seconds was on
the subject of space rocks.

These findings indicate that the members of Physics Club, with their vast
knowledge of multiple topics, are akin to the Renaissance polymaths of the
past; those of Astronomy Club could be likened to a medieval farmer whose
brain consists of nothing more than $70$ kB of farming knowledge.

##  3 Conclusion

We have definitively shown that the University of Arizona’s Physics Club is
superior over the Astronomy Club. This is obvious through the lack of
resignations, the dedication to the community and emergency preparedness, the
quantity of memes, amount of fire in demonstrations, and overall scientific
relevance.

The University of Arizona’s Physics Club would like to thank the Astronomy
Club for their promotion, generosity, and sense of humor over the years. We
would also like to thank the former officers for paving the way for the
current clubs to be successful.

## References

  * Barnes et al. (2002) Barnes, J. W., O’Brien, D. P., Fortney, J. J., & Hurford, T. A. 2002, Superiority of the Lunar and Planetary Laboratory (LPL) over Steward Observatory (SO) at the University of Arizona.  https://arxiv.org/abs/astro-ph/0204013
  * Charfman et al. (2002) Charfman, J. J., Bsc, J. B., Eriksen, K. A., et al. 2002, On the Utter Irrelevance of LPL Graduate Students: An Unbiased Survey by Steward Observatory Graduate Students.  https://arxiv.org/abs/astro-ph/0204041
  * UA Astronomy Club (2023) UA Astronomy Club. 2023, Constitution of the Astronomy Club, https://arizona.campusgroups.com
  * UA Physics Club (2022) UA Physics Club. 2022, Constitution of the Physics Club, https://arizona.campusgroups.com