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Record W36544875 · doi:10.3389/fpls.2022.1049681

Ponaredki blagovnih znamk višjega cenovnega razreda

2013· article· en· W36544875 on OpenAlexfundno aff
Sara Trstenjak, Bojan Dobovšek

Bibliographic record

VenueRevija Varstvoslovje · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Development and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Namen prispevka: Namen prispevka je opredelitev problematike ponarejanja na eni strani in odnos ljudi do nakupa blagovnih znamk visjega cenovnega razreda na drugi. Prispevek naj bi v bralcu vzbudil zanimanje za izvor izdelkov, ki jih ponujajo na trgu, prav tako naj bi ga tema pritegnila k razmisljanju in razumevanju problematike ponarejanja. Metode: Avtorja v delu uporabita deskriptivno metodo. V tem okviru na podlagi izbrane domace in tuje literature uporabita se metodo analize in interpretacije vsebine pisnih in internetnih virov. Drugi del prispevka je namenjen empiricni metodi. Z uporabo kvantitativne tehnike analizirata stanje in odnos ljudi do ponaredkov v Sloveniji. V ta namen uporabita spletno anketo, sestavljeno iz vprasanj zaprtega tipa. Nadaljujeta z nestandardiziranim intervjujem predstavnika vodilne slovenske oblacilne verige. Pridobljene podatke obdelata kvantitativno in kvalitativno. Ugotovitve: Vecina ponarejenih izdelkov prihaja iz Kitajske (Shanghai – Science and Technology Museum oziroma Underground Market, Tao Bao City, Qipo Road Market; Guangzhou), Italije (Neapelj), Turcije (Carigrad) in obmocja bivse Jugoslavije (Novi Pazar). Dokazovanje, da gre za ponaredek na trgu, je najpogosteje prepusceno kar imetniku zascitene blagovne znamke. Ker tržni inspektorat ni ustrezno usposobljen za dokazovanje, da gre za ponaredek, mora dokaze o tem predložiti imetnik zascitene blagovne znamke. Krsitve intelektualne lastnine so opredeljene kot kaznivo dejanje, kadar gre za naklepno dejanje, storjeno v komercialno korist. Omejitve/uporabnost raziskave Zaradi nacina zbiranja podatkov in vzorca raziskava odraža znacilnosti potrosnikov in njihov odnos do te problematike. Prakticna uporabnost: Izsledki clanka nam dajejo osnovo za nadaljnje raziskovanje problematike ponarejanja, hkrati pa nakazujejo na možne resitve obravnavanega problema na regionalni, nacionalni in globalni ravni. Izvirnost/pomembnost prispevka: Prispevek analizira mnenje o odnosu do nakupa ponaredkov blagovnih znamk visjega cenovnega razreda in pogled pooblascenih ponudnikov izdelkov blagovnih znamk na problematiko ponarejanja v Sloveniji. Avtorja ugotovitve aplicirata na slovenski trg ter predlagata resitve na represivnem in preventivnem podrocju.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.183
Teacher spread0.151 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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