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Record W6989924847

The changing landscape of JIBS authorship

2016· other· en· W6989924847 on OpenAlexaboutno aff

Bibliographic record

VenueRutgers University Community Repository (Rutgers University) · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101HyporeflexiaDemotionArticular cartilage damage
DOInot available

Abstract

fetched live from OpenAlex

In this study, we examine the landscape of JIBS authorship over time to assess: (1) the accessibility of JIBS to new contributors, and (2) the diversity of authors contributing to JIBS. Our analysis of author data from 1972 to 2014 shows that JIBS is becoming more accessible, as indicated by the high and sustained proportion of first-time contributors to the journal. This is also evident from the recent decline in the share of authors with multiple past JIBS publications. With regard to diversity, our findings show that JIBS has a much wider geographic scope of authors on its landscape in comparison to previous decades. This may be attributed partly to increasing travel and communication in scholarly communities, and partly to the increased migration of scholars in the recent decades. Our analysis of migration patterns of JIBS authors suggests that about 51 % of prominent international business scholars are employed outside their country of birth. Of the 49 % employed in their country of birth, 12 % are return migrants. In our sample, China, South Korea and Canada have the highest number of returnees. The USA, the UK, Germany, the Netherlands and China have the highest number of natives, whose country of birth, country of PhD-granting institution and country of university affiliation are identical.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
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 score0.131
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0040.002
Scholarly communication0.0000.000
Open science0.0050.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.199
Teacher spread0.187 · 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.

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
Published2016
Admission routes1
Has abstractyes

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