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Record W4401899315 · doi:10.20884/1.jdh.2024.24.2.4046

The Rule of Reason Approach in Discriminatory Practices: Airlines and Telecommunications Industry Sector

2024· article· en· W4401899315 on OpenAlexaff
Sharda Abrianti, Anna Maria Tri Anggraini‬, Ahmad Sabirin, Joice Chintya Mardohar, Séréna Ortigosa Fernandez

Bibliographic record

VenueJurnal Dinamika Hukum · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTelecommunicationsBusinessIndustrial organizationComputer science

Abstract

fetched live from OpenAlex

Discriminatory practices are standard in business competition and are not prohibited as long as they do not cause unfair competition. This paper will discuss three Business Competition Supervisory Commission (KPPU) decisions in 2020 related to alleged discriminatory practices committed by business actors. The subject matter in this paper is how the actions of business actors can fulfil the elements of violation and how the application of the rule of reason approach in Article 19 letter d of the Competition Law (1999) in the 2020 KPPU Decisions. This research is descriptive normative research. The data used in the book, articles, the new paper analyzed the Competition Law (1999), the Airlanes law (2009), the Electronic Information and Transactions Law (2008, amendments 2016 & 2024), and the Hajj and Umarah Law (2019), as well as interview an expert and KPPU. The interesting findings found that acts of discrimination cause obstacles in vertical business relations in different but interrelated relevant markets and often occur in the essential facilities sector. By using the rule of reason approach, KPPU found that discriminatory practices will be more effective if the business actor is in a dominant position or even occupies a monopoly position. Then, the three decisions in this discussion are equally suspected of violating Article 19 letter d on discriminatory practices. Then, related to the relevant market, the three cases have different markets, and also all three have vertical relationships with other business actors.

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)0.001
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: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.046
GPT teacher head0.358
Teacher spread0.312 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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