Bibliographic record
Abstract
Aims and Scope NCMR publishes articles that develop theory and report research on negotiation and confl ict management across levels, including interpersonal confl ict, intergroup confl ict, organizational confl ict, and crosscultural confl ict, across a range of domains, including environmental confl ict, crisis negotiations, and political confl ict, as well as across a variety of approaches, including formal and informal third party intervention, mediation, and arbitration.Theory and research related to negotiation and confl ict management are considered, such as communication, power and trust issues, ethical behavior, decision-making processes, emotions and affect, and distributive and procedural justice.The journal welcomes manuscripts that develop theory as well as ones that report original research.A variety of methods and approaches are welcome.NCMR publishes a wide range of manuscripts, including ones that initiate, extend, validate, or redirect a line of inquiry, provide a theoretically driven review, integrate research about a particular area of study or on perspectives from multiple disciplines, provide new empirical fi ndings, make theoretical contributions, and employ diverse methods.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.795 | 0.638 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".