Is the cognitive work of science grounded in tracking?

Another bump on general principles, just to remind myself.

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Bumped to the head of the list partially in response to a recent post by Tyler Cowen about human intelligence.

That's what Louis Liebenberg argues, and he's got a variety of publications and materials at Cybertracker. Here's the associated blog. Here's a blurb for his book, The Origin of Science, which you can download for free:

The Origin of Science addresses one of the great mysteries of human evolution: How did the human mind evolve the ability to develop science?

The art of tracking may well be the origin of science. Science may have evolved more than a hundred thousand years ago with the evolution of modern hunter-gatherers. Scientific reasoning may therefore be an innate ability of the human mind.

The implication of this theory is that anyone, regardless of their level of education, whether or not they can read or write, regardless of their cultural background, can make a contribution to science.

Kalahari trackers have been employed in modern scientific research using GPS-enabled handheld computers and have co-authored scientific papers.

Citizen scientists have made fundamental contributions to science. From a simple observation of a bird captured on a smart phone through to a potential Einstein, some may be better than others, but everyone can participate in science.

And here's a citizen science page.

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What it feels like tracking an animal to run it down (push it to exhaustion):

As we followed the tracks I could visualise the whole event unfolding in front of me. The kudu started to show signs of hyperthermia. It was kicking up sand and its stride was getting shorter. As it ran from shade to shade, the distances between its resting periods became shorter and shorter. In visualising the kudu I projected myself into its situation. Concentrating on the spoor I was so caught up in the event that I was completely unaware of my own state of exhaustion. As if in an almost trance-like state I could not only see how the kudu was leaping from one set of tracks to the next, but in my body I could actually feel how the kudu was moving. In a sense it felt as if I myself actually became the kudu, as if I myself was leaping from one set of tracks to the next.

Open Language Model from Allen Institute for AI

The Allen Institute for AI is building OLMo (Open Language Model):

AI2 is embarking on the creation of an open, state-of-the-art generative language model: AI2 OLMo (Open Language Model). OLMo will be comparable in scale to other state-of-the-art large language models at 70 billion parameters, and is expected in early 2024.

OLMo will be a uniquely open language model intended to benefit the research community by providing access and education around all aspects of model creation. OLMo will be a new avenue for many people in the AI research community to work directly on language models for the first time. We will be making all elements of the OLMo project accessible — not only will our data be available, but so will the code used to create the data. We will release the model, the training code, the training curves, and evaluation benchmarks. We will also openly share and discuss the ethical and educational considerations around the creation of this model to help guide the understanding and responsible development of language modeling technology.

This broad availability of all aspects of OLMo will allow the research community to directly take what we create and work to improve it. We believe that millions of people want to better understand and engage with language models, and we aim to create an environment where they actually can, leading to faster and safer progress for everyone. Our goal is to collaboratively build the best open language model in the world.

There's more at the link.

Orca 2 joins the open source movement in AI

Here's the abstract from the Orca 2 paper referenced in the video:

Orca 1 learns from rich signals, such as explanation traces, allowing it to outperform conventional instruction-tuned models on benchmarks like BigBench Hard and AGIEval. In Orca 2, we continue exploring how improved training signals can enhance smaller LMs’ reasoning abilities. Research on training small LMs has often relied on imitation learning to replicate the output of more capable models. We contend that excessive emphasis on imitation may restrict the potential of smaller models. We seek to teach small LMs to employ different solution strategies for different tasks, potentially different from the one used by the larger model. For example, while larger models might provide a direct answer to a complex task, smaller models may not have the same capacity. In Orca 2, we teach the model various reasoning techniques (step-by-step, recall then generate, recall-reason-generate, direct answer, etc.). Moreover, we aim to help the model learn to determine the most effective solution strategy for each task. We evaluate Orca 2 using a comprehensive set of 15 diverse benchmarks (corresponding to approximately 100 tasks and over 36K unique prompts). Orca 2 significantly surpasses models of similar size and attains performance levels similar or better to those of models 5-10x larger, as assessed on complex tasks that test advanced reasoning abilities in zero-shot settings. We make Orca 2 weights publicly available at aka.ms/orca-lm to support research on the development, evaluation, and alignment of smaller LMs.

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A GitHub repository of various resources for decentralized LLMs.

Internet Science

For each item, what do you predict, slice or break?

UK rainfall data digitized by volunteers [Citizen science]

Thanks to @metoffice archives, these sheets were scanned & made openly available, but how could the observations be extracted?

The answer? Ask for help: https://t.co/1Z0LcM7oBN

16,000 volunteers stepped forward during the first UK COVID lockdown to transcribe every observation.

— Ed Hawkins (@ed_hawkins) May 13, 2021

This data will be used by @markpmcc & @metoffice to improve UK rainfall reconstruction (called HadUK-Grid).

Currently the all-UK gridded reconstructions extend back to 1862. With the #rainfallrescue dataset it should be possible to go back to 1836, and earlier for some regions. pic.twitter.com/SXoqUFpYeo

— Ed Hawkins (@ed_hawkins) May 13, 2021

None of this would have been possible without the 16,000+ volunteers, and especially those who have stayed with the project the whole way (Gill, Ian, Jacqui, John B, John O, Mike, Richard, Tim). We also relied on the amazing @the_zooniverse as the citizen science web platform.

— Ed Hawkins (@ed_hawkins) May 13, 2021

We can now map out rainfall for historical extreme months that has never been possible before. For example, the Decembers in 1852 and 1853 were one of the wettest and driest on record for Scotland respectively. pic.twitter.com/LIUwcZNZNc

— Ed Hawkins (@ed_hawkins) May 13, 2021

Systematic Annotation of Literary Texts, A Shared Task

Posted to the Humanist Discussion Group:

Dear all,

We would like to draw your attention to a community-oriented initiative that will introduce a new format of collaboration into the field of Humanities: The 1st shared task on the analysis of narrative levels through annotation It is an extension of the established shared task format from the field of Computational Linguistics to Literary Studies and will commence this fall. The goal of the first stage of the (two-staged) shared task is the *collaborative creation of annotation guidelines*, which in turn will serve as a basis for the second round, an automatisation-oriented shared task. The 1st call for participation is to be sent in August 2017. The audience for the first round of the shared task are researchers interested in the (manual) analysis of narrative.

We are sending this pre-call in order to a) make you aware of this activity and b) give you the opportunity to coordinate a possible participation with your teaching or research activities in winter/fall.

Please check out our web page and feel free to point other colleagues to it. If you have questions or comments, please do not hesitate to contact us.

Best regards,

Evelyn Gius, Nils Reiter, Jannik Strötgen and Marcus Willand

Overview

https://sharedtasksinthedh.github.io/overview/

FAQ

https://sharedtasksinthedh.github.io/faq/

Leaflet

https://sharedtasksinthedh.github.io/assets/generic/Flyer_2017-04-24.pdf

From the overview:

In this talk, we would like to outline a proposal for a shared task (ST) in and for the digital humanities. In general, shared tasks are highly productive frameworks for bringing together different researchers/research groups and, if done in a sensible way, foster interdisciplinary collaboration. They have a tradition in natural language processing (NLP) where organizers define research tasks and settings. In order to cope for the specialties of DH research, we propose a ST that works in two phases, with two distinct target audiences and possible participants.

Generally, this setup allows both “sides” of the DH community to bring in what they can do best: Humanities scholars focus on conceptual issues, their description and definition. Computer science researchers focus on technical issues and work towards automatisation (cf. Kuhn & Reiter, 2015). The ideal situation, that both “sides” of DH contribute to the work in both areas, this is challenging to achieve in practice. The shared task scenario takes this into account and encourages Humanities scholars without access to programming “resources” to contribute to the conceptual phase (Phase 1), while software engineers without interest in literature per se can contribute to the automatisation phase (Phase 2). We believe that this setup can actually lower the entry bar for DH research. Decoupling, however, does not imply strict, uncrossable boundaries: There needs to be interaction between the two phases, which is also ensured by our mixed organisation team. In particular, this setup does allow mixed teams to participate in both phases (and it will be interesting to see how they fare).

In Phase 1 of a shared task, participants with a strong understanding of a specific literary phenomenon (literary studies scholars) work on the creation of annotation guidelines. This allows them to bring in their expertise without worrying about feasibility of automatisation endeavours or struggling with technical issues. We will compare the different annotation guidelines both qualitatively, by having an in-depth discussion during a workshop, and quantitatively, by measuring inter-annotator agreement, resulting in a community guided selection of annotation guidelines for a set of phenomena. The involvement of the research community in this process guarantees that heterogenous points of view are taken into account.

The guidelines will then enter Phase 2 to actually make annotations on a semi-large scale. These annotations then enter a “classical” shared task as it is established in the NLP community: Various teams competitively contribute systems, whose performances will be evaluated in a quantitative manner.

Given the complexity of many phenomena in literature, we expect the automatisation of such annotations to be an interesting challenge from an engineering perspective. On the other hand, it is an excellent opportunity to initiate the development of tools tailored to the detection of specific phenomena that are relevant for computational literary studies.

Note that while Phase 1, the creation of guidelines, must be done by experts, the application of those guidelines on a large scale could be done by "student assistants". Perhaps there could be a Phase 3 that opens out to the public of people with a strong interest in literature. Anyone who's spent a fair amount of time cruising the web looking for literary resources knows that some high-quality work is being done by people with no academic affiliation. We're now talking about so-called "citizen science", or is that citizen humanities?

Michelle Obama and the Stealth Transition: Gardens Across America

Just a reminder about the out-going First Lady. Originally posted on 8.31.12.

The way I see it, the smart money is on First Lady Michelle Obama, not to do a Hillary and go for the Big One in a later Presidential Ritual Contest (aka election). No, to do an Eleanor (Roosevelt) and have a major effect on the nation while her husband does the military strut.

How, pray tell, will she do this? you ask. With her garden, says I, with her garden.

Veggies for Health

As you may know, she’s very much interested in gardening, in particular, growing vegetables. She’s set up a garden on the Whitehouse lawn, grown veggies, had them served in the Whitehouse and has recently published a book on gardening and nutrition.

That’s her angle on gardening. Vegetables are good and good for you. They’re essential to a proper diet, and a proper diet is necessary to prevent childhood obesity.

Her interest in and commitment to gardening is deep, predating her husband’s nomination:

"Back then, it was really just the concept of, I wonder if you could grow a garden on the South Lawn?" Michelle Obama says. "If you could grow a garden, it would be pretty visible and maybe that would be the way that we could begin a conversation about childhood health, and we could actually get kids from the community to help us plant and help us harvest and see how their habits changed."

She was a city kid from Chicago's South Side who had never had a garden herself, though her mother recalls a local victory garden created to produce vegetables during World War II. One childhood photo included in the book shows Michelle as an infant in her mother's arms — the resemblance between Marian Robinson in the picture and Michelle as an adult is striking — and another depicts a young Michelle practicing a headstand in the backyard.

... After the election, she broached her idea to start the first vegetable garden on the White House grounds since Eleanor Roosevelt's victory garden in the 1940s.

Since the garden's groundbreaking in 2009 — just two months after the inauguration — she has hosted seasonal waves of students from local elementary schools that help plant the seeds. Groundskeepers and dozens of volunteers weed and tend the garden. Charlie Brandts, a White House carpenter who is a hobbyist beekeeper, has built a beehive a few feet away to pollinate the plants and provide honey that Michelle Obama says "tastes like sunshine."

So, the First Lady has a garden on the Whitehouse lawn and she’s preaching the garden gospel. Good enough.

Gardens in the Transition

The thing is, regardless of why a family or a community decides to grow a vegetable garden, the moment they start doing so, they’re also participating in the Transition Movement. By that I mean the movement started by Rob Hopkins in England and that now has groups all over the world:

The Transition Movement is comprised of vibrant, grassroots community initiatives that seek to build community resilience in the face of such challenges as peak oil, climate change and the economic crisis. Transition Initiatives differentiate themselves from other sustainability and "environmental" groups by seeking to mitigate these converging global crises by engaging their communities in home-grown, citizen-led education, action, and multi-stakeholder planning to increase local self reliance and resilience. They succeed by regeneratively using their local assets, innovating, networking, collaborating, replicating proven strategies, and respecting the deep patterns of nature and diverse cultures in their place. Transition Initiatives work with deliberation and good cheer to create a fulfilling and inspiring local way of life that can withstand the shocks of rapidly shifting global systems.

Pokémon Go and the citizen scientist

An editorial in Nature, Gotta name them all: how Pokémon can transform taxonomy:

Millions of people have spent the past week walking around. Ostensibly, they are playing the online game Pokémon Go and hunting for critters in an ‘augmented reality’ world. But as gamers wander with their smartphones — through parks and neighbourhoods, and onto the occasional high-speed railway line — they are spotting other wildlife, too.

Scientists and conservationists have been quick to capitalize on the rare potential to reach a portion of the public usually hunched over consoles in darkened rooms, and have been encouraging Pokémon hunters to snap and share online images of the real-life creatures they find. The question has even been asked: how long before the game prompts the discovery of a new species?

It’s not out of the question: success is 90% perspiration after all, and millions of gamers peering around corners and under bushes across the world can create a very sweaty exercise indeed. By definition, each Pokémon hunter almost certainly holds a high-definition camera in their hands. And there is a precedent: earlier this year, scientists reported Arulenus miae, a new species of pygmy devil grasshopper, identified in the Philippines after a researcher saw an unfamiliar insect in a photo on Facebook (J. Skejo and J. H. S. Caballero Zootaxa 4067, 383–393; 2016).

But Pokémon Go players beware. It is one thing to conquer a world of imaginary magical creatures with names like Eevee and Pidgey, and quite another to tangle with the historical complexity of the Inter­national Code of Zoological Nomenclature. So, say you do manage to snap a picture of something previously unknown to science — what then? Let Nature be your guide.

H/t 3QD.

DH Facing the Public, Sharon M. Leon in LARB

As far as I can tell, most of the debates at digital humanities – what is it? is it complicit in neoliberalism? – are about the position of digital humanities within the academy. These are conversations among scholars about the types of research they do and, less often, the courses they teach. They aren’t about how humanists address the needs and interests of people outside university walls. And yet digital technology, and the web in particular, provides a platform through which scholars can interact with the public at large. And many scholars do that through public-facing blogs. But these activities aren’t much touched upon in the DH debates.

In the most recent interview in her LARB series, Melissa Dinsmore talks with Sharon M. Leon, director of Public Projects at the Center for History and New Media (CHNM) at George Mason University. Her job is to face the public. Here’s some of her remarks.

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Can you elaborate on the differences between digital history and digital public history?

I like to make the distinction between doing history in public and doing public history. I think a lot of scholars doing digital history work are doing that work in public and making it available for an open audience to engage with, but the work of digital public history is actually formed by a specific attention to preparing materials for a particular audience — to address their questions, to engage with them, to target a real conversation with the public about a particular aspect of history. In lots of ways, public history doesn’t look like what a traditional historian would consider to be a scholarly argument; it is a little bit more subtle and much more dialogic. It has a much greater sense of shared authority and it is much less about winning a methodological argument with a community of scholars. I engage the public on the grounds that there are multiple causes of a particular event and multiple historical perspectives for understanding it. The primary difference, however, is that public history is directed at a particular audience. It’s not a “we will build it, they will come, and they might be interested” mentality. Instead, it is “I am going to do research about you, I’m going to find out the kinds of materials and prior knowledge you bring to the topic, and I’m really going to engage you.” ...

Coming back to the relevance question, public history has always been targeted and worked in that direction because it is specifically about engaging the public in a conversation about history. That work has been going on for a long time and the interesting thing about it is that just as digital work sometimes struggles for recognition and authorization in the halls of academia, public history has had a really heavy lift. There’s this weird perception that if one engages with someone who is not a credentialed scholar about scholarly questions, somehow we have diluted our commitment to inquiry. ...

How do you think the general public understands the term “digital humanities” or, more broadly, the digital work being done in the humanities (if at all)?

The public doesn’t understand the term “digital humanities,” but they do understand the work if I frame what I do as “I’m a historian who uses digital tools and methods to answer historical questions.” I think as a field our penetration into the consciousness of the public is almost nonexistent, though I imagine your series might help some. The other way to answer this question is to say that we don’t do nearly enough outreach or evaluation to have any idea what the answer is. What I have learned doing public history work is that you have to prepare, you have to know about your audience going in, you have to do the work, and you have to follow up to find out if they got anything out of it. The majority of DH work only does the middle step. They do the work. And it may not be their goal to learn what the public understands, but I think if we are going to make these claims about public relevance, we have to do all of the steps along the way so that we have some sense about our impact.

My next question has to do with public intellectualism, which many scholars and journalists alike have described as being in decline (for example, Nicholas Kristof’s New York Times essay). What role, if any, do you think digital work plays? Could the digital humanities (or the digital in the humanities) be a much needed bridge between the academy and the public, or is this perhaps expecting too much of a discipline?

The problem of the public intellectual is about the way that intellectuals frame their work for the public. It’s not really about the medium. Writing an op-ed for The New York Times for a historian or a literary scholar or a political scientist is a sort of one-shot deal that will reach a certain number of people. Whereas someone like Ta-Nehisi Coates, who is writing all the time, engaging with really important questions, has a digital presence, and actually does engage with members of the public, is a much more effective public intellectual. But I think there are lots of public intellectuals in local communities that we don’t know anything about because we aren’t in that community. Some of that work is digital work and some of it is not.

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I have a number of posts on citizen science that are relevant here.

July 4, 2016, Jupiter Day in the Solar System

Nicola Tilley in The New Yorker:

Nasa has a habit of scheduling high-stakes maneuvers to coincide with patriotic holidays. On July 4, 1997, at lunchtime, the Mars Pathfinder mission successfully landed Sojourner, the first Martian rover. Eleven years ago, on the same date, the Deep Impact probe successfully collided with the comet Tempel 1, an achievement that the astronomer Iwan Williams described as being “like a mosquito hitting a 747.” And on Monday, at just before 9 p.m. Pacific Standard Time, after a thirty-five-minute engine burn, nasa’s Juno spacecraft successfully reached the end of its five-year journey and began circling Jupiter. For the engineers at the Jet Propulsion Laboratory, in Pasadena, California, it was not only Independence Day but also Orbital Insertion Day. As the operations team confirmed that the burn had gone to plan, all of mission control rose to its feet. To a standing ovation, a visibly relieved Scott Bolton, the mission’s principal investigator, said, “We just did the hardest thing nasa’s ever done.”

“This was a one-shot deal,” Bolton had said earlier. Not only was Juno moving faster than any human-made object ever has when its engine fired—more than a hundred and sixty-five thousand miles per hour—but its onboard electronics were operating in what J.P.L.’s Heidi Becker described as “a spray of radiation bullets”: charged electrons spiralling up and down the lines of Jupiter’s magnetic field at almost the speed of light. It was the mission’s riskiest moment since launch.

The mission's most challenging scientific objective is to map Jupiter's magnetic field:

The gas giant’s magnetosphere is nearly twenty thousand times more powerful than Earth’s, resulting in spectacular polar auroras larger than our entire planet. And its magnetic field extends so far into space that, if it glowed in visible light, Jupiter would appear to be twice the size of the full moon in our night sky. While Galileo captured stunning surface images of swirling ammoniac storms, Juno’s mission is to peek beneath the gaseous veil to see inside Jupiter. Scientists believe that the planet’s intense magnetism is generated by the churning of a deep interior ocean of hydrogen, under such intense pressure that the element becomes a shimmery liquid. (“Like a mirror, it reflects light, so if you were immersed in it, you wouldn’t be able to see anything,” Caltech’s David Stevenson explained in 2011, on the one-year anniversary of Juno’s launch.) A detailed map of the resulting field would offer researchers the clues they need to understand this hidden ocean’s depth and currents.

Citizen science:

By this point, nasa is aware that a lofty goal, without visual imagery to accompany it, will not engage the public’s imagination. The agency’s solution is JunoCam, a device adapted from previous Mars missions. Freed from the burden of scientific responsibility, amateurs and enthusiasts will be able to vote online to determine where JunoCam points and which features it captures. “It will provide the very first views of Jupiter’s poles, and the most incredible closeup views of the planet ever seen,” Bolton said. “I expect we will probably discover some new moons, too. But it’s really a public camera.” Already, JunoCam’s discussion boards are alight: six-year-old Bee wants more photos of the Red Spot, while Hogarth-11 is voting for a closer look at greenish dots near Jupiter’s equator.

Fans and Scholars Working on the History of Science Fiction

Stefana Forlini, Uta Hinrichs, and Bridget Moynihan, The Stuff of Science Fiction: An Experiment in Literary History, DHQ 2016, vol 10, #1.

Abstract: This article argues for a speculative, exploratory approach to literary history that incorporates information visualization early on into, and throughout, the research process. The proposed methodology combines different kinds of expertise — including that of fans and scholars in both literary studies and computer science — in processing and sharing unique cultural materials. Working with a vast fan-curated archive, we suggest tempering scholarly approaches to the history of science fiction (SF) with fan perspectives and demonstrate how information visualization can be incorporated into humanistic research processes, supporting exploration and interpretation of little-known cultural collections.

A Shared-Expertise Approach to Cultural Analysis

In her recent work, How We Think, N. Katherine Hayles suggests that Digital Humanities (DH) research offers new opportunities for creative collaborations across disciplines and with "expert amateurs" beyond "academic walls" [Hayles 2012, 36]. Such collaborations require that we acknowledge the value of different kinds of expertise, welcome cross-pollination of approaches and promote open access to rare materials and to analytical activities. In this article, we argue for a collaborative, shared-expertise approach to literary and/or cultural collections and showcase our own take on such an approach. The work we present is the result of the collaboration between an expert amateur who compiled one of "the most important research archives" of SF [Latham 2010, 161] and scholars in both literary studies and computer science.

In an attempt to reconsider numerous neglected specimens of proto/early SF and to devise a DH approach to literary history suited to popular genres, our project specifically aims

• to investigate how the Bob Gibson anthologies of speculative fiction — unique, hand-crafted and fan-curated anthologies of SF’s "great unread" [Moretti 2000, 54] — can contribute to scholarly assessments of the evolution of SF, and
• to develop information visualizations that enable researchers, students, fans, and the general public to explore the collection from different perspectives, promoting fluid movement between close and distant reading.

Visualizations are key to our collaborative and exploratory approach. Rather than using visualizations solely to display the final "results" of our research, we are experimenting with evolving interactive visualizations in tandem with our research questions and ongoing investigations of Gibson’s untapped collection of little-known materials. The visualizations are thus integral to our research "process", shaping and being shaped by our research questions and ongoing findings, and are not simply tools used as a means to an end. This exploratory approach is necessary because very little is known about the primary materials we are investigating. Moreover, we want to make visible our research process as it is impacted by digital tools and to remain open to unforeseen questions and research avenues that arise through our first-hand interactions with the collection and with the developing visualizations.

In describing this process, our article makes two main contributions: we outline our emergent method for the study of early SF in the context of the Gibson Collection, adapting Franco Moretti’s [Moretti 2005] evolutionary approach to genre, and we demonstrate how integrating information visualization early on in the research process can support exploration and guide the interpretation of vast, largely unknown literary collections. We begin by introducing the Gibson anthologies and their unique characteristics before describing our theoretical approach to investigating and classifying their material contents, and the design considerations underlying our visualizations. Because the focus of this paper is primarily on the value of visualizations employed throughout the research process, we describe our initial visual explorations and findings as well as new iterations of our visualizations as they evolved. Finally, we identify the benefits and limitations of our approach to early SF as it has developed so far and outline future steps. 

* * * * * *

The rest of the article is HERE.

Toward a Fan-Based Research Collaboratory

Cross posted at The Valve

Despite some reservations about fan scholarship -- e.g. I've seen pointless edit wars at Wikipedia & pros are adept at pointless quarrels as well -- I'm seriously thinking about an initiative to see if fans are interested in doing at least some of the descriptive work I call for in the piece on cultural evolution I recently did for the National Humanities Center (cf. this "quasi-festo" for naturalist criticism, and this piece on "Kubla Khan"). I see little prospect that academy-based scholars will under take such work in the near term. The sort of descriptive work I have in mind is not obviously subordinate to an inquiry into the "meaning" of a text. That pretty much means that the work is not unpublisheable on its own; there's no obvious way to earn professional credit for doing it.

But fans may well be interested in doing such work, though on the texts that interest them. And those texts are only rarely going to be canonical high culture texts. And that's just fine with me. I've done such work on manga and cartoons and would have no problem with doing it on episodes of, e.g. Buffy the Vampire Slayer or Star Trek (any generation).

I've recently been doing quite a bit of work on Sita Sings the Blues, an animated film by Nina Paley, which I discuss in the Humanities Center post. As some of you may know, the film is done in four different visual styles. So I've made a table with a column for each style and then gone through the film from beginning to end and briefly annotated each segment in the proper column. You can find that table online in a Google docs file here. One of those segments, the Agni Pariksha, is done in a fifth style. I've gone through that segment an annotated each "shot" or sequence within it. You can find that here. In principle each of the some 60+ segments in the film could be described at the level of detail I've used in the Agni Pariksha segment.

In fact, one could easily describe a film frame-by-frame. Would that be worthwhile? In some cases, yes, and in some cases no. It depends. There's really no way of knowing until the work's been done in at least some cases and we can take a look at it.

It's clear to me that such descriptive work is a necessary precondition to a deeper knowledge of texts, whether written, filmed, or videotaped. All the cognitive psych and evolutionary psych and neuro-psych in the world is not going to accomplish what can only be accomplished through description. If the pros aren't going to do the work, then it's up to the fans. If the fans get into it, then in a decade or two the pros will have no choice but to follow or simply to drop off the edge of the earth.

Seel also, this post on Tvtropes.org.

Wuthering Heights, Vampires, Handbooks, and Citizen Science

Heathcliff as vampire wannabe? Why didn't I think of that? Fortunately others have.

Over at The Literature Network, kev67 asked (in Nov 2012):

I was just wondering whether Wuthering Heights was some sort of proto-vampire book when in the last chapter Nelly herself wonders whether Heathcliff is a ghoul or a vampire. I was surprised as I did not think vampires had been discovered till later. I have not watched any of the Twilight films (and I don't intend to neither) but it struck me there were some similarities between Wuthering Heights, Twilight, Buffy the Vampire Slayer and other vampire films and television series. Heathcliff can stand bright sunlight; bibles, wooden crosses, garlic and holy water might annoy him but would not be sufficient to ward him off; and although driving a wooden stake through his heart would kill him, so would other methods of execution. However, there are some similarities: Heathcliff is evil (like most vampires). Heathcliff and Catherine continue to walk the Earth after death and do not find rest. Heathcliff has no hope of salvation, neither does he want it. Heathcliff's idea of heaven is close to torment. Heathcliff's love for Catherine is eternal (rather like some vampire love stories). Heathcliff's love for Catherine is rather chaste. Heathcliff is tall, strong, rather dark with long, black hair. Heathcliff forms one point of a love triangle with Catherine as the apex (a bit like Twilight I believe).

The good folks at Shmoop – "We speak student" – are on the case. Here's the lead to their Wuthering Heights material:

Edward and Bella, meet Heathcliff and Catherine.

That's right: before The Walking Dead, Twilight, Buffy the Vampire Slayer, and The Vampire Diaries, there was Wuthering Heights.

At first glance, Heathcliff may not resemble the vampires that you've grown to know and love (or hate), but he's got a lot more going for him than most of 'em. Just saying.

Wuthering Heights, published in 1847, revolves around the passionate and destructive love between its two central characters, Emily Brontë's headstrong and beautiful Catherine Earnshaw and her tall, dark, handsome, and brooding hero/devil, Heathcliff.

Forget the romantic candlelit dinners, the wine, and the roses. Catherine and Heathcliff's love exists on an entirely different plane: one that involves ghosts, corpses, the communion (or possession) of souls, and revenge. And, speaking of revenge, Heathcliff—who harbors more than one grudge against his adoptive family, the love of his life, and his neighbors—manages to make every revenge drama look like kid's play.

And to seal the deal, "Reading Wuthering Heights gives you bragging rights over all your friends who think that the whole vampire thing started with Buffy. Suckas."

* * * * *

I'm thinking a couple of things.

First, the connection is valid. I assume that proper scholarly work has been done on this connection, tracing themes and connections, that sort of thing. If not, get on it, someone!

Second, I'm guessing that these two sites, Shmoop, and The Literature Network, are aimed at high school students and lower level undergraduates and community college students (and their teachers). And we've got Cliff's Notes and Spark Notes and others serving the same market. They all have basic stuff about literary texts, mostly canonical ones.

How much of the material at these sites could be consolidated into consensus handbooks of materials about these texts? These sites are commercial enterprizes and so, I assume, would be reluctant to give up their stuff to an open-access resource. But, they're already giving their stuff away on the net. Why don't they all draw on the same body of standard material, material that furthermore has been vetted by scholars – assuming you can find first-rate scholars willing to do this. These sites would also be useful for the casebook industry.

I've been calling for handbooks for awhile. My point is that we've got the seeds of that already on the net.

Third, this leads us to citizen science. There's lots of 'fan'-created stuff on the web. Some of high quality. This Wuthering Heights site, by Paul Thompson, is excellent. I found it when looking for a timeline of events in the story. Thompson's done quite a bit of sleuthing on this. There's handbook quality material lurking here.

But how do we put it all together? And just who is "we"? Does literary academia want to commit proud suicide or does it want to enter the 21st century and engage the large population of people who are interested in literature (though they might not give a crap about high theory)?

Does hot water freeze faster than cold?

In some circumstances, it does. The question is a old one, dating back at least to Aristotle, and turns out to be surprisingly complex. This paper is a good study in the subtleties of getting clear answers from Nature.

Hot water can freeze faster than cold?!? 

Monwhea Jeng

Physics Department, Box 1654, Southern Illinois University Edwardsville, Edwardsville, IL, 62025 

We review the Mpemba effect, where intially hot water freezes faster than initially cold water. While the effect appears impossible at first sight, it has been seen in numerous experiments, was reported on by Aristotle, Francis Bacon, and Descartes, and has been well-known as folklore around the world. It has a rich and fascinating history, which culminates in the dramatic story of the secondary school student, Erasto Mpemba, who reintroduced the effect to the twentieth century scientific community. The phenomenon, while simple to describe, is deceptively complex, and illustrates numerous important issues about the scientific method: the role of skepticism in scientific inquiry, the influence of theory on experiment and observation, the need for precision in the statement of a scientific hypothesis, and the nature of falsifiability. We survey proposed theoretical mechanisms for the Mpemba effect, and the results of modern experiments on the phenomenon. Studies of the observation that hot water pipes are more likely to burst than cold water pipes are also described.

H/t Faculty of Language.

Citizen Science: Help untangle the connections among the brain's neurons

I'm knee-deep in reading a NYTImes Mag article about Sebastian Seung, a Princeton neuroscientist who hopes to map the connections among neurons in the human brain. The human connectome, as it's called, has recently been elevated to Holy Grail status within neuroscientist. While I doubt that it deserves that status, sure, why not map all the connections and see what you get?

In the process Seung has developed a game that allows citizens – that's you and me – to help:

In 2012, Seung started EyeWire, an online game that challenges the public to trace neuronal wiring — now using computers, not pens — in the retina of a mouse’s eye. Seung’s artificial-­intelligence algorithms process the raw images, then players earn points as they mark, paint-by-numbers style, the branches of a neuron through a three-dimensional cube. The game has attracted 165,000 players in 164 countries. In effect, Seung is employing artificial intelligence as a force multiplier for a global, all-volunteer army that has included Lorinda, a Missouri grandmother who also paints watercolors, and Iliyan (a.k.a. @crazyman4865), a high-school student in Bulgaria who once played for nearly 24 hours straight. Computers do what they can and then leave the rest to what remains the most potent pattern-recognition technology ever discovered: the human brain.

Ultimately, Seung still hopes that artificial intelligence will be able to handle the entire job. But in the meantime, he is working to recruit more help. In August, South Korea’s largest telecom company announced a partnership with EyeWire, running nationwide ads to bring in more players. In the next few years, Seung hopes to go bigger by enticing a company to turn EyeWire into a game with characters and a story line that people play purely for fun. “Think of what we could do,” Seung said, “if we could capture even a small fraction of the mental effort that goes into Angry Birds.”

No doubt we will learn something from the connectome of a single brain, but what? What generalizations can we make from the connectome of a single brain? 10 brains, 100 brains, a thousand, ten-thousand? And these are necessarily brains of dead people. It would be nice to follow the connectome of a single brain over time, year by year, month by month, day by day...hour by hour? Imagine, for a moment, that we could do that. Much of the value in that effort would be in tracking the connectivity of individual neurons from one moment to the next. To do that, though, we need to be able to assign a unique identifier to each neuron and then track that identifier from one measurement period to the next. How would we do that?

And then there is this:

Eve Marder, a prominent neuroscientist at Brandeis University, cautions against expecting too much from the connectome. She studies neurons that control the stomachs of crabs and lobsters. In these relatively simple systems of 30 or so neurons, she has shown that neuromodulators — signaling chemicals that wash across regions of the brain, omitted from Seung’s static map — can fundamentally change how a circuit functions. If this is true for the stomach of a crustacean, the mind reels to consider what may be happening in the brain of a mouse, not to mention a human.

I'm thinking that if all goes well, in a decade or so the connectomitrists will examine their work, rethink, and do something else, something that we and they could not otherwise have imagined.

* * * * *

Here's an old post of mine–well, the post isn't so old, but it consists of notes that are at least a decade old–that talks a bit about neural connectivity and identity in the context of direct brain-to-brain communication.

You too can spot sprites in the sky for science

From the NYTimes:

Armed with sensitive cameras and radio telescopes, Mr. Ashcraft hunts for sprites — majestic emanations of light that flash for an instant high above the thunderheads, appearing in the shapes of red glowing jellyfish, carrots, angels, broccoli, or mandrake roots with blue dangly tendrils. (Weather buffs call the tall, skinny ones “diet sprites.”) No two are alike.

And they are huge — tens of miles wide and 30 miles from top to bottom. But because they appear and vanish in a split-second, the naked eye tends to perceive them only as momentary flashes of light. It takes a high-speed camera to capture them in detail.

Depending on his skill and luck and the presence of storms, Mr. Ashcraft might get one or two sprite images a night, or more than 300. From June through August this year, he captured sprite images on 29 nights.

One of a growing corps of citizens who advance the scientific process in every field from astronomy to zoology, he sends his best images to Steven A. Cummer, a professor of electrical and computer engineering at Duke University who leads a multicenter project called Phocal, for Physical Origins of Coupling to the Upper Atmosphere by Lightning.

“We happily take images captured by anyone, either our own cameras or those of citizen scientists like Thomas Ashcraft,” Dr. Cummer said. A goal is to capture sprite images from multiple locations to triangulate their position relative to the lightning that creates them.

From “Distant” Reading to Crowdsourcing, or, the Rise of Citizen Scholars

Distant reading of ALL texts, yes. But also, every text must be read by a human reader. This will require crowd-sourcing† from skilled amateur readers. This is the only way, for example, we’ll be able to deal with the mass of popular culture texts that must be accounted for.

Distant reading and dark matter

One of Moretti’s arguments in favor of “distant” reading is that most of the texts that have been written never receive consideration under the standard (now traditional) regime of literary criticism. Under that regime reading is restricted to a relatively small handful of canonical texts. What of all those unread texts, the “dark matter” of literary culture (to borrow a metaphor from astrophysics)? How do we take account of them? Yet they must play some role in literary culture. How are we going to understand that role if we don’t read them?

The problem, Moretti pointed out, is that no one has time to read all of the texts. One critic can read several hundred, a thousand texts, or so. But not the 10s of thousands of novels published in, say, the nineteenth century alone. Moretti’s solution? Use computers to scan through all those texts and analyze them in this way or that.

I have no problem with this computer mediated “distant” reading as Moretti calls it. no problem at all. But, as a result of undertaking a close look at Matthew Jockers’ Macroanalysis I’ve reached the tentative conclusion that in fact a much larger fraction, if not all, of the texts in that unread dark matter must be read by humans. Perhaps not in the style of old-fashioned close reading, but they must be read in order to identify features and properties that computers cannot (yet) identify.

Michael Nielson: The Artist and the Machine

From the post, which is about images produced through scientific instrumentation:

While Super-realism isn’t new, that doesn’t mean it’s yet in the artistic mainstream. Many people don’t consider works such as the Hubble Extreme Deep Field or the light-in-a-bottle video to be art. (I would not be surprised if this includes the creators of those works.) Even works more explicitly artistic in intent, such as Water in Suspense, are viewed as borderline. But I believe that each of these works reveals a new aesthetic, an aesthetic generated by the scientific principles underlying the phenomenon being represented. And insofar as they reveal a new aesthetic, I believe these works are art.

He concludes:

Super-realism has grown rapidly in the past twenty to thirty years. Three forces are driving that growth.

First, far more people can access and learn to use scientific instruments. Recall Juan Geuer and his virtuoso home-made laser light show. There are people building everything from home-made bubble chambers to balloons exploring the upper atmosphere. These are not isolated curiosities, but rather part of a rapidly expanding social phenomenon that has been called by many names: the DIY movement, citizen science, the Maker movement. Whatever it is, it’s growing...

Second, the data being taken by many of these instruments is being shared openly, online. In the 1980s if a scientist used a telescope to take a photograph, likely no more than a few dozen people would ever touch the photographic plate. Now more than a billion people can download data from the Hubble Telescope, and find new ways to visualize it...

Third, we’re collectively building a powerful suite of tools to reveal these new worlds. For example, as I write there are more than 25,000 open source visualization projects available on the code repository GitHub. Most of those projects are, of coure, experiments that will be abandoned. But there are also many powerful tools that give people incredible abilities to make and reveal beauty. It’s no wonder Super-realism is flowering.

Story-tellers say that reality is often stranger and more interesting than fiction. I believe this is true for all art. The reason is that nature is more imaginative than we, and as we probe deeper into nature, we will continue to discover new aesthetics and new forms of beauty. I believe these new aesthetics will stimulate art for decades or centuries to come.

Alan Liu: Reengaging the Humanities

Alan Liu week continues at New Savanna. Now I want to look at an interview he gave to Scott Pound at Amodern: Reengaging the Humanities. While the interview is worthwhile in its entirety I’ll select passages where Liu’s thinking (usefully) intersects with my own.

First, though, I want to cite a biographical passage which speaks to attitude and intuition. While talking about Bruno Latour’s interrogation of critique in the name of compositionalism Liu informs us that he’s “the son of a structural engineer and descended from a whole clan who were allowed to immigrate to the U.S. because they were engineers and builders.”

Yes.

And I’m the son of a chemical engineer who spent his professional career in the coal business. Engineering is about designing things and building them.* I used “Speculative Engineering” as the title for the preface to my book on music (Beethoven’s Anvil) because I wanted to emphasize the constructive nature of my enterprise. I talked about the building blocks I played with as a child and posed the question: “How does the nervous system design and construct music?” (xiii). I think about literary texts and systems of texts in the same way: How are they built?

Returning to Liu, he has quite a bit to say about critique and compositionism. Note his use of engineering language in the following passage:

Critique and compositionism are best understood as arcs in a common cycle of thought, whether at the level of individual projects or of longer generational agendas. Think of it this way: in any project there are tactically important moments when critique is constructive, e.g., at the beginning when assessing what is wrong with precedents or in the middle after the first prototype. Equally, there are tactically shrewd moments when composited methods and viewpoints are constructive, e.g., when the architect pitches a project to a client and has to incorporate the client’s views, when the architect then has to adjust plans in response to the structural engineer, and when the engineer subsequently has to adjust plans in response to the contractors, not to mention the tactically decisive construction workers who actually wield the hammers). It’s just that neither critique nor compositionism has a right to rule as the “last word” in the process–the terminal stage, the end result, the payoff, the final record. In the humanities, I feel, we have fallen into the rut of thinking that interpretive discourse (e.g., a critical essay) should be the final statement of a project, and, further, that critique should be the final payoff of interpretation. [Emphasis mine, WLB] But what if we were to position interpretive discourse and critique elsewhere in the cycle of thought that goes into a project? Compositionism would then not be antithetical to critique; it would include the arc of critique, and vice versa, as part of the rolling launch of thought.

Perhaps we should remind ourselves that the primacy of interpretation is a relatively recent development in our disciplinary history, mostly post World War II, and that literary culture managed to function for centuries without a guild of professional interpreters.

Primer on Neural Nets

Michael Nielsen is writing a book on neural nets and deep learning and he's posting chapters to the web. You can access the first chapter here, which uses the recognition of hand-written numerals as its problem domain. You can get access to the rest of the chapters by contributing to his Indigogo campaign.

About Michael Nielsen:

My work is motivated by the creation of tools to help people think better, either individually or in groups. Put another way, I’m interested in cognitive tools and in collective intelligence. 

Open science 

I believe that publicly funded science should be open science, and from 2008-2012 I worked as an advocate for open science. You can get the flavour of my work on open science from my talk at ted.com, or in my op-ed in the Wall Street Journal. I’ve developed these ideas at length in my essay on The Future of Science and in other essays. I’ve also written a book about collective intelligence and open science. It was named one of the best books of 2011 by the Financial Times and by the Boston Globe...