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Record W6922056875 · doi:10.13016/m22805130

Effect Of New Security Regulations On Airline Concentration

2011· other· en· W6922056875 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository at the University of Maryland (University of Maryland College Park) · 2011
Typeother
Languageen
FieldSocial Sciences
TopicEducation Methods and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMonopolyCompetition (biology)Quarter (Canadian coin)Market shareTerrorismOligopolyMarket structure

Abstract

fetched live from OpenAlex

An entire set of new airport security regulations were implemented globally after September 11, 2001 terrorist attack on U.S.A. The effect of these new security regulations on competition level of airline industry is analyzed here for international flights arriving and departing from American airports, using enplanement data from 1990 to 2000. It is found here that, new regulations slightly reduced the competition level of the airline industry. However, the change is very subtle. Additionally, these new regulations helped some airline organizations to manipulate the market in their favor. In the forth quarter of 2001 the monopoly rate suddenly and unusually went up around the world. However, the situation persists for only one quarter and this particular issue was resolved from 2002 only. It is proposed that in the oligopoly market the big airline firms were able to use economies of scale, in various forms, to gain market share immediately after the terrorist attack.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.196
Threshold uncertainty score0.994

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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