Bibliographic record
Abstract
Citation (2006), "List of Contributors", Yammarino, F.J. and Dansereau, F. (Ed.) Multi-Level Issues in Social Systems (Research in Multi-Level Issues, Vol. 5), Emerald Group Publishing Limited, Bingley, pp. xi-xii. https://doi.org/10.1016/S1475-9144(06)05022-3 Publisher: Emerald Group Publishing Limited Copyright © 2006, Emerald Group Publishing Limited Book Chapters About the editors List of Contributors Overview: multi-level issues in social systems Multi-level fit: an integrative framework for understanding hrm practices in cross-cultural contexts An organizational perspective on multi-level cultural integration: human resource management practices in cross-cultural contexts Integrating HRM practices into a multi-level model of culture: culture's values, depth, and strength Multi-level fit: complexity, values, and climate Continuous learning in organizations: a living systems analysis of individual, group, and organization learning Continuous learning: why is it still an issue? A multi-level inquiry and elaboration: continuous learning within and across organizations, groups, and individuals Continuous learning about continuous learning: clarifying and expanding a multi-level, living system's analysis The importance of the common family background for the similarity of divorce risks of siblings: a multi-level event history analysis Sibling effects on divorce: common family background, common genetic heritage, or continuing interaction among adult siblings Multi-level event history analysis for a sibling design: the choice of predictor variables Additional Thoughts about The Importance of Common Family Background for the Similarity of Divorce Risks of Siblings Industry–university intellectual property dynamics as a multi-level phenomenon Industry–university relationships and the context of intellectual property dynamics: the case of ibm Industry–University Technology Transfer: Moving The Research Agenda Forward Industry–university intellectual property in context: framing the deal, and dealing with the frame(s) The LAMPE Theory of Organizational Leadership “Breaking the frame” even farther: complexity science and lampe theory Some ideas about testing processual theories About the Authors
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.746 | 0.733 |
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".