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Record W4205497103 · doi:10.1111/ele.13949

Can I afford to publish? A dilemma for African scholars

2021· article· en· W4205497103 on OpenAlexaff
Addisu Mekonnen, Colleen T. Downs, Edu O. Effiom, Mohamed Kibaja, Michael J. Lawes, Patrick A. Omeja, Fanomezana M. Ratsoavina, Onja H. Razafindratsima, Dipto Sarkar, Nils Chr. Stenseth, Colin A. Chapman

Bibliographic record

VenueEcology Letters · 2021
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsCarleton UniversityUniversity of Calgary
FundersNational Research FoundationWoodrow Wilson International Center for Scholars
KeywordsPublishingPublicationDilemmaOpen access publishingPaymentPolitical scienceBusinessPublic relationsLibrary scienceComputer scienceLawFinance

Abstract

fetched live from OpenAlex

With open-access publishing authors often pay an article processing charge and subsequently their article is freely available online. These charges are beyond the reach of most African academics. Thus, the trend towards open-access publishing will shift the business model from a pay-wall model, where access to literature is limited, to a pay-to-publish one, where African scholars cannot afford to publish. We explore the costs of publishing and the ability of African scholars to afford to publish via open access in top journals. Three-quarters of the 40 top ecology journals required payment for open-access publishing (average cost $3150). Paying such fees is a hardship for African scholars as grant funding is not available and it is not feasible to pay the fees themselves as salaries are low. We encourage funders and publishers to facilitate an equitable publishing model that allows African scholars to make their research available through open-access publishing.

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)0.009
metaresearch head score (Gemma)0.076
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.076
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0260.103
Science and technology studies0.0000.000
Scholarly communication0.0030.000
Open science0.0020.001
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 head0.434
GPT teacher head0.525
Teacher spread0.092 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations64
Published2021
Admission routes1
Has abstractyes

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