Pat Savage

@patrickesavage

Author: Comparative Musicology (academic.oup.com/book/62353; open access) Director: @compmusiclab.bsky.social Host/PI @manyvoices.bsky.social Rutherford Discovery Fellow @U Auckland Assoc. Prof. @Keio U Music, evolution, diversity He/him Tangata tiriti

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Pat Savage@patrickesavage· 11d

Pedagogically, I prefer mine (osf.io/preprints/ps...), but I have to admit this is funnier.

Figure 3. Stylised figure showing my proposed reading/writing order to maximise efficiency given diminishing marginal returns as you read academic research in greater detail. While analogous approaches can be applied to many books, review articles, and humanities articles (e.g., Adler & van Doren, 1972), this approach is particularly suitable for empirical scientific journal articles. Meme from Adam & Walker (2019).

Pat Savage@patrickesavage· 13d

Amazing follow-up video: www.youtube.com/watch?v=7-W6...

Screenshot from "How I Made the Gen Alpha Melody" video by Carl E. Martin.
Captions: "to the Brits. You win. You'll never win this [FIF world cup], but you won this ["gen alpha melody" cup]

Pat Savage@patrickesavage· 14d

Loved @gene.meme's article on copyright issues in the ubiquitous "Gen Alpha Melody". However, as a musicologist researching copyright (academic.oup.com/book/62353/c...), I have to point out that the shared (non-copyrightable) chord progressions obscure a lot of (copyrightable) melodic variation.

Visualisation of comparative analysis of three examples shown in Carl Martin's "Gen Alpha Melody" YouTube video show that two are very similar ("It's Only Love" and "So Am I" 65% identical) while "APT" and "So Am I" are not so similar (34%).

Examples of historical legal cases centred on melodic infringement. <45% identical melodies are usually not judged as infringing (green), while more than this can be judged infringing (red) or not, depending on context.

Pat Savage@patrickesavage· 14d

Was just reminded (through a great chat with @eselster.bsky.social) of this fantastic album - treat yourself to a listen! folkways.si.edu/songs-of-the...

Spotify playlist showing the first 7 tracks from the album "Song of the Earth: Astonishing and Rare Voices"

Pat Savage@patrickesavage· 14d

Amazing video and article! However, the similar chord progressions are obscuring important differences. Some of these melodies are not so similar (e.g., APT vs. So Am I: 34%) while some are very similar (e.g., So Am I vs. It's Only Love: 65%): For details, see academic.oup.com/book/62353/c...

Figure 6.2 from my book, "Comparative musicology" (https://academic.oup.com/book/62353/chapter/554463078#556813890)

Comparisons of three copyright case excerpts demonstrating decreasing melodic similarity. Plaintiff appears in top, defendant on bottom. Melodies are transposed to the common tonic of C to enhance comparability, and identical notes are coloured in red.a (a) The chorus melodies of “Hachigatsu no Rainy” (top) and “M.A.K.E.” (bottom) are 100 per cent identical. (b) The openings of “He’s So Fine” (top) and “My Sweet Lord”) show high (>60 per cent) melodic similarity. (c) The “signature phrases” of “Got to Give it Up” and “Blurred Lines” show moderately low (<50 per cent) melodic similarity. (d) These three cases and thirty-seven more visualised in terms of their melodic similarity (y-axis; see Chapter 2) and overall similarity as measured through perceptual experiments (x-axis). Note that the similarity values from a–c are not identical to those shown in d because a–c are short excerpts from the longer sections analysed.

Pat Savage@patrickesavage· 16d

+1 for "The Professor Is In" And shameless plug for my own guide for new grad (and undergrad) students: "How and why to read (and write and publish) academic research": doi.org/10.31234/osf...

How and why to read (and write and publish) academic research

Patrick E. Savage

Abstract: This article is designed to concisely teach undergraduate and new graduate students lessons in reading and writing I have learned in my past two decades as a university student, teacher, and researcher (including through publishing, retracting, correcting, and republishing articles in outlets with varying levels of “impact” and publication fees). Don’t just start at the beginning of an academic article/book and try to read straight to the end! Instead, I recommend starting by reading the title(s)/author(s) and abstract(s), then the figures, reading the Discussion section, and skimming/spot-checking the references, peer reviews, and data (e.g., spreadsheets, audiovisual stimuli, surveys), if available. Only once you have done this and evaluated whether it seems worth your time do I recommend deciding whether to read every word of some/all sections/chapters (and any accompanying supplementary material) or digging deeper into reanalysing/replicating the data. I recommend writing accordingly so that most of your key information will be conveyed even if your reader only gets through your title, abstract, and figures. I discuss various strategies to improve your own academic reading/writing and the broader culture of academia, from practical (e.g., formatting and tracking references and citations using Zotero and Google Scholar, asking constructive questions rather than self-promoting comments, publishing using Peer Community In Registered Reports, using the “sandwich thesis” model for PhD dissertations) to philosophical (e.g., ethical issues in authorship, citation, AI, publishing, and funding). I explain the intended goals of academic research (to create and distribute valuable new knowledge) and perverse incentives that lead us astray from these goals (e.g., chasing prestige and funding). I conclude by contemplating if and how we should dismantle the current extortionary academi…

Pat Savage@patrickesavage· 18d

Time for another note about the Trump administration’s approach to funding US science. But let me make something clear right up front. When I talk to people about this subject (and that includes some journalists as well) and say what I'm about to at the end of this paragaph I am sometimes met with disbelief. But I mean what I say and I am trying my best to say what I mean: The Trump administration hates academic science funding, full stop. They hate where that money goes, and they hate who it goes to. They want to keep all that money for themselves, to hand out to favored cronies who can help them get elected and to steer yet more money and more power back into their hands.

That’s it. That’s the story. They are naturally not putting it in those words, but instead talking about “gold standard science” and the “reproducibility crisis” and funding “bold inquiry” for “transformational breakthroughs”. This is all bullshit, and it’s important to realize that.

Pat Savage@patrickesavage· 19d

Just gave a quick last-minute interview for RNZ about what makes songs catchy. You can listen to the recording here: www.rnz.co.nz/national/pro...

What makes some songs stick in your head?
From Afternoons, 28 minutes ago

24 July 2026

Whether music is good or not is entirely subjective .. or is it? What makes some songs catchier than others? We wanted to get an expert opinion. Dr Patrick Savage knows a bit about this; he is a musicologist at the University of Auckland and joins Jesse.

Pat Savage@patrickesavage· 28d

New interview on Radio NZ about how and why humans evolved to make music (spoiler alert: I believe it’s primarily for social bonding) www.rnz.co.nz/national/pro...

What is the driving force behind humans and music?

That is a question that Auckland University musicologist Dr Patrick Savage has been working to answer.

Pat Savage@patrickesavage· Jul 10

Luxon to NZ researchers: #53 #Waiata100

Lyrics to “Expert in a dying field”

How does it feel
To be an expert in a dying field?
And how do you know
It’s over when you can’t let go?

Pat Savage@patrickesavage· Jul 10

Mānawatia a Matariki! Loved Radio NZ's top 100 waiata countdown. A few of these (Hope, Kai Tangata, Tūtira Mai Ngā Iwi) were discussed by Danya Pavlovich and myself on our episodes of @manyvoices.bsky.social podcast. Check those out for more lore and bangers that didn't make RNZ's list!

Me talking about my favourite NZ song, "Hope" by Fat Freddy's Drop and how I play basketball with its singer, Dallas Tamaira

Danya Pavlovich talking about her favourite contemporary waiata, Alien Weaponry's "Kai Tangata", a metal fusion take on the ancient Māori custom of cannibalism

Pat Savage@patrickesavage· Jul 10

What 6 songs would you choose to represent your language? Watch/listen to season 1 of @manyvoices.bsky.social podcast on YouTube/Spotify/Podcast to hear guests share songs from their 8 languages. And let me know if you have guests or ideas to suggest for Season 2 and beyond! many-voices.com

Languages/guest for the 8 episodes of season 1 of Many Voices: A world music podcast:
1. Cantonese (Psyche Loui)
2. te reo Māori (Danya Pavlovich)
3. Maasai (Mark Lenini Parselelo)
4. Japanese (Gakuto Chiba)
5. Hebrew (Nori Jacoby)
6. Guaraní (Brenda Suyanne Barbosa)
7. Italian (Andrea Ravignani)
8. US/NZ English (Patrick Savage w/ Maika & Kazushi)

Pat Savage@patrickesavage· Jul 10

The countdown is on! www.rnz.co.nz/national

Pat Savage@patrickesavage· Jul 8

Totally rewrote my AI section of my guide to academic reading/writing (osf.io/preprints/ps...) - now subtitled "AI-generated fabrications as academic misconduct". Any feedback on these guidelines/figures before I formally update the preprint? @mcxfrank.bsky.social @russpoldrack.org

Some universities, including my own, have essentially capitulated to BigAI, signing agreements with corporations like OpenAI (often without faculty consultation) or opening “two-lane” assessment where students are allowed or encouraged to use genAI (Curtis, 2025). I predict this will end badly.

Since I can no longer rely on university academic integrity policy on AI, here is my own policy. Sadly, it is much stricter than my earlier policies, since students, authors, and BigAI corporations took advantage of my and others’ previous willingness to give the benefit of the doubt:
Never use AI to generate or alter academic text (including references, slides, or scripts for oral presentations) or images.
Always include an AI statement in any academic work (including student assignments or journal articles) stating whether or not you used AI for any part of your work. If you did use it, clearly describe exactly which parts were done by AI and which were done by you.
In grey areas (e.g., AI translation of text you wrote in a different language), be very cautious and very explicit in declaring how you mitigated potential issues (e.g., back-translating the translation into your own language and manually checking and correcting any mistranslations).
Failure to include an AI statement or signs of undisclosed AI use will result in an automatic failure/rejection of the assignment/article, and may raise broader questions/referrals regarding the academic integrity of your other work.

AI-generated fabrications as academic misconduct

The first version of this guide I posted in September 2024 (https://osf.io/download/cme3d/?revision=1) didn’t mention artificial intelligence. At my students’ request, I added a section titled “On coexisting with AI in academic research”, which originally suggested that “if you are comfortable admitting how you used AI, you are probably OK using it, so be sure to transparently disclose if and how you use AI.” In retrospect, although the importance of transparent AI declaration still holds, the part about being “probably OK” was somewhat näive.

Since then, genAI has transformed academia and the world more rapidly than any previous technology I’ve experienced in my lifetime. In my experience, these changes have not been for the better (Fig. 5). I’ve become increasingly disillusioned and distressed by the uncritical and unethical ways I’ve seen people in universities (including my own students, colleagues, and administrators) and corporations using and promoting genAI to replace rather than assist their own thinking (Guest et al., 2026; Baker, 2026; Goldstein, 2026; Nadaff & Quill, 2026). The main ways genAI has affected my own life have mostly been negative, sucking up my own time and happiness as an academic being forced to read/evaluate/fix bland AI-generated texts that appear superficially plausible but on closer inspection are full of errors and fabrications (“hallucinations”).

Figure 5. My adaptation of the “For the better, right?” meme (Abrams, 2021) to incorporate a headline about OpenAI CE Sam Altman believing AI will “change the world” (Eastwood, 2024).

I am sensing a growing consensus among colleagues that AI tools have many legitimate uses when carefully supervised, checked, and corrected by humans (e.g., transcription, coding, finding relevant papers, feedback on draft manuscripts), but a clear line should be drawn between such uses and AI-generated text or images, which are not acceptable in academic settings except in special circumstances. For example, a leading AI expert, Stanford Professor Michael Frank (2026), proposes that genAI “agents should not directly touch the text of the paper. Paper text should be written by a human. If agents write text, it's still far too easy for them to make things up (especially references) and to write text that is superficially correct but unmoored to the actual human research activities.”

Frank’s comment that genAI tends to “make things up” is the core of my concern. Fabricated references have emerged as one of the easiest ways to detect AI-generated writing (Fig. 6). Traditionally, academics have required that factual claims are supported either by new evidence or by citations to previous evidence to allow readers to independently verify the source of the claim. The “References” section of this and other papers is thus not merely a formality, but a form of scientific data and core component of academic integrity. Just as fabricating data in scientific figures or quotations in interviews is considered an unacceptable form of research misconduct, in at least some cases, “Hallucinated citations produced by generative artificial intelligence may constitute research misconduct” (Resnik & Hosseini, 2026; see Nadaff & Quill 2026).

Figure 6. Example of characteristic attributes of an AI-fabricated (“hallucinated”) reference. Source: Nadaff & Quill (2026)

Importantly, AI fabrications are by no means limited to references - these are just some of the easiest to catch and prove. AI-fabricated figures, such as the infamous rat “dck” (Fig. 7) are increasingly leading research papers to be retracted. I have had the distinct displeasure in recent years to personally witness numerous examples of AI-fabricated images, quotations, and references in research articles and student assignments. Particularly obvious examples included fabricated quotations attributed to me in journals that don’t even exist!

Figure 7. An AI-generated figure published in a peer-reviewed journal article that was swiftly retracted when readers pointed out many unreliable aspects, including the giant rat “dck” with 4+ “testtomcels” (see McFall-Johnsen, 2024).

Pat Savage@patrickesavage· Jul 5

Need some musical for grading? Try my inspirational playlist: open.spotify.com/playlist/0Lb...

Grading playlist:

ABC
All Night Long
I Hate AI
Blatant Plagiarism
Before He Cheats
typos
I Feel So Free (Citation Needed)
Glassworks: IV. Rubric
I Want It That Way
Fitter Happier

Pat Savage@patrickesavage· Jul 2

This slide I made last year feels sadly relevant ("Silencing Indigenous / humanities voices will only strengthen the global assault on science")

My slide from an invited symposium at the Max Planck Institute for Evolutionary Anthropology showing attacks on Indigenous / humanities / science research by Dawkins, Trump, etc., concluding "Silencing Indigenous / humanities voices will only strengthen the global assault on science

Pat Savage@patrickesavage· Jul 2

🌏🎶 Special Many Voices: A world music podcast episode! 🎶🌏 The Season 1 finale ends with two very special guest hosts - my own kids! They interviewed me about my own NZ/US musical culture to make me see what it's like on the other end of the microphone: youtu.be/N9IZixq1pOs

Title screen:
Many Voices: A world music podcast
Dr. Patrick Savage (NZ/US English)
+ special guest hosts Maika & Kazushi

introducing Sinners and O Brother, Where Art Thou movies about Americana music

*Chapters*
00:00 Introduction
01:54 #1 (sing): Misty (youtu.be/lJXLqAutql4)
05:51 (bonus traditional): I Lied To You (from "Sinners") - Miles Caton (youtu.be/S7jo5Cr6WUA)
07:15 #2 (traditional): I'll Fly Away (from "O Brother Where Art Thou") - Gillian Welch & Alison Krauss (youtu.be/sdRdqp4N3Jw)
09:03 #3 (contemporary): Hope - Fat Freddy's Drop (youtu.be/kXvZf7TmT3k)
11:29 #4 (happy): Christmas Eve (from "The Calvin & Hobbes Suite) - Lyrics by Bill Watterson, music composed by Patrick Savage, sung by the Amherst College Zumbyes and Bluestockings (youtu.be/eOnLKQ35EkQ)
13:43 #5 (sad): It's Quiet Uptown (from "Hamilton") - Lin-Manuel Miranda (youtu.be/I5N7xCSOrQg)
15:33 (bonus dance): Naatu Naatu (from "R.R.R.") - M.M. Keeravaani (youtu.be/4_eEgJhsBMo)
16:19 #6 (dance): Thriller - Michael Jackson (youtu.be/sOnqjkJTMaA)
17:18 Thriller - performed by the Amherst College Zumbyes at the Lincoln Centre in the 2007 International Championship of Collegiate A Capella (youtu.be/-7hwc6yTbjI)
19:05 Broader thoughts on music and science
23:56 (bonus kid category: video game music): Super Mario Bros. theme song - Koji Kondo (youtu.be/-avspZlbOWU)
25:15 (bonus) Mario skit by the Zumbyes: youtu.be/L1pXRC02q5o
25:50 (bonus) theme from "Hollow Knight" - Composed by Christopher Larkin, performed by Maika Savage (youtu.be/0PQBtRV7Tes | youtu.be/r6PuACnHkNY)
27:25 (bonus) Hornet (from "Hollow Knight") - Composed by Christopher Larkin, performed by Kazushi Savage (youtu.be/apHbW1oO-Vs | youtu.be/7xkM8mWC4Kk)
29:46 Post-credit scene: Between Two Mammoths (Amherst College President Michael Elliot interviews Zumbyes Business Manager Ashley Yuen Z'25) (youtu.be/VTF3AeLsCkY)

Between 2 Mammoths with Ashley Yuen '25: Season 3, Episode 4

Pat Savage@patrickesavage· Jul 1

I'm super-proud of my daughter for participating in her first science fair! Thanks to @janinepaynter.bsky.social and @lcsnz.bsky.social for the tips on etiolation and data visualisation (she properly credited you in the Acknowledgments like a good scientist 🥰) #NZPieceOfScience

Maika Savage with her science fair presentation titled “Let’s grow! Making plants grow faster with sunlight”

The Acknowledgments section reads:
“My family for supporting me through the whole project and giving me lots of helpful suggestions” “Dr Janine Paynter for suggesting that I look into etiolation”
“Dr Lucy Stewart for advice on data visualisation”
“Special thanks to my grandfather who got me this board and the room temperature monitor”

Pat Savage@patrickesavage· Jun 29

I meant no harm. I most truly did not.
But I had to grow bigger. So bigger I got.
I biggered my factory. I biggered my roads.
I biggered my wagons. I biggered the loads
of the Thneeds I shipped out. I was shipping them forth
to the South! To the East! To the West! To the North!
I went right on biggering... selling more Thneeds.
And I biggered by money, which everyone needs.

Pat Savage@patrickesavage· Jun 26

Important data visualization poll! I’m trying to convince my 12yo daughter she should not truncate the y-axis for her first science fair poster. Others think I’m being too hardcore. Thoughts? 2 versions for comparison

Pat Savage@patrickesavage· Jun 22

I deeply resent that GenAI has polluted my work life with shit. I agree with @mhmdhsini.bsky.social & Resnick: "citations that point to non-existent work...should be classified as a form of research misconduct...invalid citations amount to data fabrication..." We need to start cracking down hard.

"citations that point to non-existent work in reviews and bibliometric studies should be classified as a form of research misconduct if the references serve as data that directly support findings and conclusions[10]. In this case, the invalid citations amount to data fabrication"
Quoted in Nature, "Hallucinated citations are polluting the scientific literature. What can be done?"

Pat Savage@patrickesavage· Jun 22

Watched Sheep Detectives last night - amazing! 🐏🕵️ Trying to match character voices with their actors (e.g., Patrick Stewart, Bryan Cranston, Rhys Darby) made we wonder if musicians are better at this task. Turns out, we are! doi.org/10.1371/jour...

Sebastian from Sheep Detectives (left) was voiced by Bryan Cranston, who played Walter White in Breaking Bad (right)

Pat Savage@patrickesavage· Jun 19

I'm trialing the podcast hosting service Buzzsprout for my latest podcast episode. In particular, I wanted a place to publish the transcript along with the episode for those who wanted to read the discussion without watching/listening to the whole thing. many-voices.buzzsprout.com/2625456/epis...

#7: Italian music with Prof Andrea Ravignani (Sapienza University Rome)
podcast episode plus opening transcript

Then you must acknowledge that some of what we do when listening, producing, perceiving music is related in part to our genes, but that doesn't explain that genes explain most of the things.

Patrick Savage

Yeah. Right. And I was actually interested, in our study, we compared music and genes and languages and I was expecting music to map pretty well with the genes and it actually didn't. So it's nice kind of to see that they can be separate as well as the same. Obviously there's some relationship between the genes and the music at some level. yeah, getting to see what percent and how and why is I think fascinating for me and I think for all of us doing this kind of research. I think we'll talk a lot about it this week at the conference.

Andrea Ravignani

Or it could explain almost zero inter-individual variability or variability within human populations, but we find that there is something in human genes that can explain our capacity for musicality a bit more than other mammals. I wouldn't be super surprised of that.

But I'm not a Chomskian. Don't get me wrong!

Song choice (31:34)

Patrick Savage

There's two final questions. So one was if you could only choose one of or music today to kind of represent you and your culture or identity, whatever that is. It's tough question, but which would you choose?

Andrea Ravignani

I would definitely go with John Powell because, yeah, because, well, he's English and, you know, even though they did the Brexit thing, we still love you, dear Brits, so come back. And, no, but also I think his music if you keep listening to it, connects really a lot of strands of Western music from orchestral classical and romantic music. There is a lot of pentatonic scales and a lot of borrowing from Celtic and Viking stuff, but also more southern European percussions and polyrhythms and so on and so forth. So definitely John Powell.

Patrick Savage

Great. I wouldn't have picked that coming in, but now that you've explained it, it makes a…

Pat Savage@patrickesavage· Jun 18

🌏🎶 New @manyvoices.bsky.social podcast episode with @andrearavignani.bsky.social covers music from his homeland, from the Italian anti-fascist anthem "Bella Ciao" to pan-European instrumental music like Bach and John Powell's "How To Train Your Dragon", and beyond: www.youtube.com/watch?v=Qfju...

Pat Savage@patrickesavage· Jun 18

"Chaos in the brickyard" is a classic. I highlight a quote from it in my guide to "How and why to read (and write and publish) academic research" (osf.io/preprints/ps...)

Another useful metaphor is thinking of individual journal articles as bricks, and PhD dissertations and the broader academic literature in general as edifices of knowledge built from these bricks. Resist any pressure you might experience to think of individual articles/bricks as the end product themselves, or that simply publishing a certain number of journal articles is all you need to get a PhD/job or contribute to society. As Bernard Forscher warned in his parable, “Chaos in the brickyard”:

Once upon a time…there was an activity called scientific research and the performers of this activity were called scientists. In reality, however, these [scientists] were builders who constructed edifices, called explanations or laws, by assembling bricks, called facts…. And then it came to pass that a misunderstanding spread among the brickmakers…. The brickmakers became obsessed with the making of bricks…. It even was suggested that the production of a suitable number of bricks was equivalent to building an edifice and therefore should entitle the industrious brickmaker to assume the title of builder and, with the title, the authority…saddest of all, sometimes no effort was made even to maintain the distinction between a pile of bricks and a true edifice. (Forscher, 1963)

Pat Savage@patrickesavage· Jun 18

Meme from Heavyweights (1995)
“Who’s Seymour Butts?”
“Nobody’s seen more butts than you, Uncle Tony”

Pat Savage@patrickesavage· Jun 17

Perfect juxtaposition on my feed with “huge molasses tank”

“Huge molasses tank explodes” old headline

Pat Savage@patrickesavage· Jun 17

she stated that pre- and post-study fMRI data was provided by participants themselves

Pat Savage@patrickesavage· Jun 17

New human cultural universal dropped

“Nearly all cultures believe that a ladybird is lucky!”

Pat Savage@patrickesavage· Jun 13

Extremely damning stuff strongly suggesting (among many other disturbing things) that Pinker allowed Epstein to shape the letter Pinker wrote for Epstein’s legal defense, received $10k for the letter, and later lied about it 😮