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Record W4224948655 · doi:10.5204/mcj.2882

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2022· article· en· W4224948655 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueM/C Journal · 2022
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

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Introduction 2021 was the year that NFTs got big—not just in value but also in terms of the cultural consciousness. When digital artist Beeple sold the portfolio of his 5,000 daily images at Christie’s for US$69 million, the art world was left intrigued, confused, and outraged in equal measure. Depending on who you asked, non-fungible tokens (NFTs) seemed to be either a quick cash-grab or the future of the art market (Bowden and Jones; Smee). Following the Beeple sale, articles started to appear indicating that the film industry was abuzz for NFTs. Independent filmmaker Kevin Smith was quick to announce that he planned to release his horror film Killroy Was Here as an NFT (Alexander); in September 2021 the James Bond film No Time to Die also unveiled a series of collectibles to coincide with the film’s much-delayed theatrical release (Natalee); the distribution and collectible platforms Vuele, NFT Studios, and Mogul Productions all emerged, and the industry rumour mill suggests more start-ups are en route (CurrencyWorks; NFT Studios; NewsBTC). Blockchain disciples say that the technology will solve all the problems of the Internet (Tewari; Norton; European Business Review); critics say it will only perpetuate existing accessibility and equality issues (Davis and Flatow; Klein). Those more circumspect will doubtless sit back until the dust settles, waiting to see what parts of so-called web3 will be genuinely integrated into the architecture of the Internet. Pamela Hutchinson puts it neatly in terms of the arts sector: “the NFT may revolutionise the art market, film funding and distribution. Or it might be an ecological disaster and a financial bubble, in which few actual movies change hands, and fraudsters get rich from other people’s intellectual property” (Hutchinson). There is an uptick in the literature around NFTs and blockchain (see Quiniou; Gayvoronskaya & Meinel); however, the technology remains unregulated and unstandardised (Yeung 212-14; Dimitropoulos 112-13). Similarly, the sheer amount of funding being put into fundamental technical, data, and security-related issues speaks volumes to the nascency of the space (Ossinger; Livni; Gayvoronskaya & Meinel 52-6). Put very briefly, NFTs are part of a given blockchain system; think of them, like cryptocurrency coins, as “units of value” within that system (Roose). NFTs were initially rolled out on Ethereum, though several other blockchains have now implemented their own NFT frameworks. NFTs are usually not the artwork itself, but rather a unique, un-copyable (hence, non-fungible) piece of code that is attached, linked, or connected to another digital file, be that an image, video, text, or something else entirely. NFTs are often referred to as a digital artwork’s “certificate of authenticity” (Roose). At the time of writing, it remains to be seen how widely blockchain and NFT technology will be implemented across the entertainment industries. However, this article aims to outline the current state of implementation in the film trade specifically, and to attempt to sort true potential from the hype. Beginning with an overview of the core issues around blockchain and NFTs as they apply to film properties and adjacent products, current implementations of the technology are outlined, before finishing with a hesitant glimpse into the potential future applications. The Issues and Conversation At the core of current conversations around blockchain are three topics: intellectual property and ownership, concentrations of power and control, and environmental impact. To this I would like to add a consideration of social capital, which I begin with briefly here. Both the film industry and “crypto” — if we take the latter to encompass the various facets of so-called ‘web3’ — are engines of social capital. In the case of cinema, its products are commodified and passed through a model that begins with exclusivity (theatrical release) before progressing to mass availability (home media, streaming). The cinematic object, i.e., an individual copy of a film, is, by virtue of its origins as a mass product of the twentieth century, fungible. The film is captured, copied, stored, distributed, and shared. The film-industrial model has always relied on social phenomena, word of mouth, critical discourse, and latterly on buzz across digital social media platforms. This is perhaps as distinct from fine art, where — at least for dealers — the content of the piece does not necessarily matter so much as verification of ownership and provenance. Similarly, web3, with its decentralised and often-anonymised processes, relies on a kind of social activity, or at least a recorded interaction wherein the chain is stamped and each iteration is updated across the system. Even without the current hype, web3 still relies a great deal on discourse, sharing, and community, particularly as it flattens the existing hierarchies of the Internet that linger from Web 2.0. In terms of NFTs, blockchain systems attach scarcity and uniqueness to digital objects. For now, that scarcity and uniqueness is resulting in financial value, though as Jonathan Beller argues the notion of value could — or perhaps should — be reconsidered as blockchain technology, and especially cryptocurrencies, evolve (Beller 217). Regardless, NFT advocates maintain that this is the future of all online activity. To questions of copyright, the structures of blockchain do permit some level of certainty around where a given piece of intellectual property emerged. This is particularly useful where there are transnational differences in recognition of copyright law, such as in France, for instance (Quiniou 112-13). The Berne Convention stipulates that “the subsistence of copyright does not rest on the compliance with formal requirements: rights will exist if the work meets the requirements for protection set out by national law and treaties” (Guadamuz 1373). However, there are still no legal structures underpinning even the most transparent of transactions, when an originator goes out of their way to transfer rights to the buyer of the accompanying NFT. The minimum requirement — even courtesy — for the assignment of rights is the identification of the work itself; as Guadamuz notes, this is tricky for NFTs as they are written in code (1374). The blockchain’s openness and transparency are its key benefits, but until the code can explicitly include (or concretely and permanently reference) the ‘content’ of an NFT, its utility as a system of ownership is questionable. Decentralisation, too, is raised consistently as a key positive characteristic of blockchain technology. Despite the energy required for this decentralisation (addressed shortly), it is true that, at least in its base code, blockchain is a technology with no centralised source of truth or verification. Instead, such verification is performed by every node on the chain. On the surface, for the film industry, this might mean modes of financing, rights management, and distribution chains that are not beholden to multinational media conglomerates, streamers like Netflix, niche intermediaries, or legacy studios. The result here would be a flattening of the terrain: breaking down studio and corporate gatekeeping in favour of a more democratised creative landscape. Creators and creative teams would work peer-to-peer, paying, contracting, servicing, and distribution via the blockchain, with iron-clad, publicly accessible tracking of transactions and ownership. The alternative, though, is that the same imbalances persist, just in a different form: this is outlined in the next section. As Hunter Vaughan writes, the film industry’s environmental impact has long been under-examined. Its practices are diverse, distributed, and hard to quantify. Cinematic images, Vaughan writes, “do not come from nothing, and they do not vanish into the air: they have always been generated by the earth and sun, by fossil fuels and chemical reactions, and our enjoyment of them has material consequences” (3). We believe that by watching a “green” film like Avatar we are doing good, but it implicates us in the dirty secret, an issue of “ignorance and of voluntary psychosis” where “we do not see who we are harming or how these practices are affecting the environment, and we routinely agree to accept the virtual as real” (5). Beyond questions of implication and eco-material conceptualisation, however, there are stark facts. In the 1920s, the Kodak Park Plant in New York drew 12 million gallons of water from Lake Ontario each day to produce film stock. As the twentieth century came to a close, this amount — for a single film plant — had grown to 35-53 million gallons per day. The waste water was perfunctorily “cleaned” and then dumped into surrounding rivers (72-3). This was just one plant, and one part of the filmmaking process. With the shift to digital, this cost might now be calculated in the extraction of precious metals used to make contemporary cameras, computers, or storage devices. Regardless, extrapolate outwards to a global film industry and one quickly realises the impact is almost beyond comprehension. Considering — let alone calculating — the carbon footprint of blockchain requires outlining some fundamentals of the technology. The two primary architectures of blockchain are Proof of Work (PoW) and Proof of Stake (PoS), both of which denote methods of adding and verifying new blocks to a chain. PoW was the first model, employed by Bitcoin and the first iteration of Ethereum. In a PoW model, each new block has a specific cryptographic hash. To confirm the new block, crypto miners use their systems to generate a target hash that is less than or equal to that of the block. The systems process these calculations quickly, as the goal is to be “the first miner with the target hash because that miner is the one who can update the blockchain and receive crypto rewards” (Daly). The race for

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.847
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.217
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it