MétaCan
Menu
Back to cohort
Record W2511362561

The Internet, Facebook, smart phones and intellectual property rights: a happy combination?

2017· article· en· W2511362561 on OpenAlexaboutno aff
Estelle Derclaye

Bibliographic record

VenueNottingham ePrints (University of Nottingham) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsInternet privacyThe InternetPopulationIntellectual propertyQuarter (Canadian coin)AdvertisingWorld Wide WebWorld populationBusinessPolitical scienceComputer scienceSociologyGeographyLaw
DOInot available

Abstract

fetched live from OpenAlex

2014 was the 25th birthday of the World Wide Web (WWW) and as of 30 June 2014, 3,035,749,340 (ie around 3 billion and 35 million) people were connected to the Internet so a bit more than half the population of the planet. There were around 1.70 billion active smart phones in the world at the end of 2014. Users check their devices on average every 6.5 min or 150 times per day. There is around the same amount of monthly active Facebook users in the world as there are smart phones (1.39 billion as of the third quarter of 2014). There is therefore no denying the growing pervasiveness and thus influence that the Internet generally (static or mobile) and all its applications especially Facebook, in short Web 2.0 and beyond, have on the world’s population. Research also shows that when people are more socially involved, “they are happier and healthier, both physically and mentally.” So it would be logical to think that the connectedness that the Web 2.0 enables makes people happier. However, as we shall see in this paper, the story is more complex. The person generally considered the founder of the WWW, Tim Berners-Lee, did not patent his ‘invention’. He wanted it to be free for all to use. By contrast, smart phones makers and providers of many applications, such as Facebook, heavily rely on exclusive IP rights (IPR). For instance, in 2012, Facebook owned around 812 patents, namely 20 of its own, 750 purchased from IBM, and the remaining others acquired from other tech giants. So even if the WWW as such is IPR-free, many of its applications including mobile apps (software) are greatly IPR-dependent. Smart phones incorporate hundreds if not thousands of patent, designs, copyright and other satellite IPR such as rights on topographies of semi-conductor chips, database rights and trademarks. IPR encourage innovation by giving exclusive rights to inventors. This is called the incentive theory of intellectual property. Since patents, designs and copyright eventually expire, it may be said that the IP system encourages inventors and creators, or at least some of them, to keep innovating including by making minor incremental innovations and updates. However, this is not the same as saying that current IP laws and policies target well-being; only that IPRs incentivise new and original products, which are assumed to foster economic growth.In most civil law countries, IP laws aim to protect the natural rights of inventors and creators (their livelihood, name and reputation). The focus here is, therefore, on the well-being of creators and inventors and not on a more general view of well-being, that is also that of users. From the incentive theory flows the so-called technological neutrality of IP law. This principle comes from the liberalist ideology which underlies modern, Western and Western-influenced, IP laws, but is an ideology which does not go without saying. There is a limit to technology neutrality: inventions, designs and works which are immoral or against public policy often cannot be protected by IPR. However, this subject-matter which is excluded from IP laws is generally rather strictly interpreted. Inventions and creations related to information and communication technologies (ICTs) such as those applying to smart phones and Facebook typically would not fall within that exclusion. Most ICTs, unlike new foodstuffs, chemicals and pharmaceuticals, are not otherwise vetted by public authorities.When scrutiny does happen, it is often after the patent has been granted. As some ICTs such as smart phones, tablets, social networking, apps, and online video games can have negative effects on well-being -- and in some cases quite severe ones, -- it would seem logical to apply a system similar to the approval of new foodstuffs to them. Why is what we ingest or inhale carefully trialed before commercialisation but not ‘what our mind absorbs’? Moreover, based on empirical research on technologies’ effects on well-being, should we have a well-being enhancing or at least not well-being reducing condition in our IP laws? To find out, we begin by examining what the literature in other fields -- chiefly in psychology -- has found in relation to the effects of ICTs on well-being. Other related fields can then add to the discussion , especially philosophy. This article embarks in the first of these two cross-disciplinary enquiries to see what lessons can be drawn for the IP framework in general.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0050.016
Scholarly communication0.0220.049
Open science0.0010.011
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0240.007

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 head0.036
GPT teacher head0.266
Teacher spread0.230 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueNottingham ePrints (University of Nottingham)Same topicPrivacy, Security, and Data ProtectionFrench-language works237,207