MétaCan
Menu
Back to cohort

Characteristics of Commercial Leaflets Sandwiched in Newspaper (Part 5) : Distribution Volume and Trends of Commercial Leaflets by Year

2018· article· en· W2901186696 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Korea Technical Association of The Pulp and Paper Industry · 2018
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperDistribution (mathematics)AdvertisingQuarter (Canadian coin)Consumption (sociology)Order (exchange)BusinessMarketingClothingAgricultural economicsMathematicsEconomicsGeographyPolitical scienceSociologySocial scienceFinanceLaw

Abstract

fetched live from OpenAlex

In order to analyze the distribution trends of leaflets in newspapers, the relationship between the number of leaflets and the consumer price index was examined according to year and category of business. The distribution volume of leaflets has been decreased every year. On 2017, it is estimated to have decreased by 46% compared to 2013 and will continue to decrease in the future. Distribution of large size leaflets has been decreasing every year. The leaflets that are widely distributed are A4 and A8 sizes. The major distribution period of leaflets was the second quarter (April-June), where consumption and activity are active. The amount of leaflets has been decreasing year by year. Large stores, and the business of electronics, education, and clothing showed a high consumption tendency of leaflets. The industry of food and beverage showed the slight decrease on the consumption of leaflets, and the construction, automobiles and other leaflets were distributed constantly every year. There may be various reasons on the decrease of leaflets. They include the development of information technology and other public relations media replacing the role of leaflets, the change of advertisement methods, or the business situation getting worse.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.296

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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