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Record W3204012633 · doi:10.1002/leap.1422

Expanding <scp><i>Nature</i></scp>: <scp>Product line</scp> and brand extensions of a scientific journal

2021· article· en· W3204012633 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.

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

Bibliographic record

VenueLearned Publishing · 2021
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsReputationPublishingProduct (mathematics)Brand extensionAdvertisingField (mathematics)BusinessMarketingBrand managementSociologyPolitical scienceMathematicsSocial science

Abstract

fetched live from OpenAlex

Abstract Academic publishers now market their most prestigious journals as commercial brands. This paper investigates this trend in the scholarly publishing market, by analyzing how the successive owners of the journal Nature have capitalized on its reputation to generate additional profits to those already accumulated through university library subscriptions. Two branding strategies of the journal Nature are analyzed: the first one, product line extension, consists in extending the Nature brand in the same product category, by creating an ever‐increasing number of derived Nature journals; the second one, brand extension, consists in extending the Nature brand to other categories of products and services, such as academic rankings, sponsored supplements, feature advertisements, or webinars and trainings. The Nature brand leveraging strategy has been imitated by many other journal publishers. These branded products and services are well suited to the particular dynamics of the scientific field, which is based on the continuous quest for recognition. They are thus sold at all stages of the research cycle, from writing grants to popularizing research results, to scientists and academic institutions competing to accumulate symbolic capital. In this respect, academic publishers that engage in scholarly journal branding contribute to the transformation of the scientific ‘community’ into a scientific market.

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)0.051
metaresearch head score (Gemma)0.575
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0510.575
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0360.146
Science and technology studies0.0020.001
Scholarly communication0.0590.008
Open science0.0030.002
Research integrity0.0000.003
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 head0.333
GPT teacher head0.485
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