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Record W4375867964 · doi:10.5210/fm.v28i5.12682

Platformization of Korean Internet portals toward mega-platforms: A historical approach

2023· article· en· W4375867964 on OpenAlex
Dal Yong Jin

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFirst Monday · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMerge (version control)The InternetInformation and Communications TechnologyBusinessWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

This paper documents the evolution of Korea’s digital platforms. By using a historical approach in tandem with platformization — helpful in determining the causes behind the changing processes of new technologies — we examine the advancement of digital platforms. The digital platform era can be divided into three significant periods based on major technical advancements and corporate transformations, including the early construction of ICT infrastructure between the mid-1990s and early 2000s; the early platformization period of Internet portals amidst the smartphone revolution between the mid-2000s and mid-2010s; and the duopoly market of Naver and Kakao from the mid-2010s, after the merge of Daum and Kakao, to the present. Multiple causes led to the advent of digital platforms, both in terms of technologies and systems. Power relations developed between several major players, such as the government, corporations, and global forces. This work ultimately describes the relationship between sociocultural transitions and accompanying structural changes in digital platforms and relevant policies.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.617

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 studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.196
Teacher spread0.160 · 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