Novel Perspectives on Inclusion Across Levels of Analysis: Work Groups, Organizations and Industries
Bibliographic record
Abstract
Framing inclusion as a competitive advantage has become standard business practice in recent years. This symposium explores the causes and consequences of inclusion across various levels of analysis: the workgroup (Roberson et al.), the organization (Sitzmann et al. and Kossek et al.), and the industry (Pozner & Woolley). The papers examine factors that contribute to inclusion, including individuals’ positions in networks (Roberson et al.), organizational work-family support structures (Kossek et al.), and interactions with others through industry communities (Pozner & Woolley). Additionally, the papers explore a range of consequences both for individuals’ well-being (e.g., outcomes of caregivers, Kossek et al.) and for firm performance (e.g., firms’ labor productivity, Sitzmann et al.). The symposium will conclude with discussant Lisa Nishii, whose remarks – in conjunction with the papers presented in the session – will further the audience’s understanding of the causes and consequences of inclusion across workgroups, organizations, and industries. A Social Network Approach to Understanding Workgroup Inclusion Author: Quinetta M. Roberson; Michigan State U. Author: Victor Elijah Blocker; Michigan State U. Author: Dorothy R. Carter; Michigan State U. Author: Kristin Cullen-Lester; U. of Mississippi Author: Justin Matthew Jones; U. of Florida Attaining Productivity via Inclusive Workplaces: Experiences of Inclusion, Anger, and Achievement Author: Traci Sitzmann; U. of Colorado, Denver Author: Mijeong Kwon; U. of Colorado, Denver Author: Shoshana Schwartz; Christopher Newport U. Rethinking Family Supportive Organizations Toward a Diversity, Equity, and Inclusion Perspective Author: Ellen Ernst Kossek; Purdue U. Author: Benjamin R. Pratt; U. of Central Oklahoma Author: Hoda Vaziri; U. of North Texas Author: Eden King; Rice U. Author: Brenda A. Lautsch; Simon Fraser U. Crafting Inclusion: Making Space for New Voices in Craft Author: Jo-Ellen Pozner; Santa Clara U. Author: Jennifer Woolley; Santa Clara U.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".