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Record W2906070738 · doi:10.1111/ncmr.12143

<i><scp>NCMR</scp></i>'s First Decade: An Empirical Examination

2018· article· en· W2906070738 on OpenAlexaff
Michael Groß, Eric J. Neuman, Wendi L. Adair, Mallory Wallace

Bibliographic record

VenueNegotiation and Conflict Management Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNegotiationScope (computer science)DemographicsConflict managementEmpirical examinationContent analysisContent (measure theory)Empirical researchComputer scienceSociologySocial scienceEpistemologyBusinessDemography

Abstract

fetched live from OpenAlex

Abstract This retrospective offers an empirical analysis of NCMR author demographics, scholarly content, and article impact over the journal's first decade. Results highlight the journal's broad content and scope including distinct networks of knowledge communities focused on both conflict and negotiation and their subfields. Authors interpret existing network patterns and offer future direction as NCMR continues to evolve and grow within the changing landscape of negotiation and conflict management research.

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)0.010
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.010
Science and technology studies0.0030.002
Scholarly communication0.0070.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.137
GPT teacher head0.442
Teacher spread0.305 · 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.

Study designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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