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Record W4214561205 · doi:10.1177/20563051221077032

Bridging the Open Web and APIs: Alternative Social Media Alongside the Corporate Web

2022· article· en· W4214561205 on OpenAlexaff
Jack Jamieson, Naomi Yamashita, Rhonda McEwen

Bibliographic record

VenueSocial Media + Society · 2022
Typearticle
Languageen
FieldComputer Science
TopicMobile Crowdsensing and Crowdsourcing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWorld Wide WebSocial mediaThe InternetWeb 2.0Computer scienceWeb syndicationAmbiguityData scienceBusiness

Abstract

fetched live from OpenAlex

Concentrations of power over the internet among a small number of corporate platforms have motivated attempts to build alternative social media. Using the contemporary internet routinely involves relying on a small number of dominant corporate platforms. In reaction against this centralization of power, there are many attempts to build alternative Web technologies that reconfigure the internet’s power structures and enact their own values. However, given the entrenchment of large corporate platforms, this typically involves co-existing with rather than replacing them, at least in the present. Accordingly, it is important to investigate challenges arising when alternative social media operate alongside and even within the systems to which they propose an alternative. We investigate this through an empirical study of the IndieWeb, a community of personal websites with social networking features including syndication to and from corporate platforms. Using GitHub data, we study the development of a tool for this syndication called Bridgy, focusing on its relationship with the Facebook API. By identifying breakdowns in this relationship, we identify the following challenges: translating differing logics between the open Web and APIs, occasional ambiguity in Facebook’s presentation of privacy settings, and ongoing precarity due to API updates. Our analysis illustrates the reality of maintaining alternative technical systems as part of present-day infrastructures and generates insights for building socially empowering technologies for the future.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0020.003
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 head0.045
GPT teacher head0.255
Teacher spread0.211 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations7
Published2022
Admission routes1
Has abstractyes

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