Addressing the Trust “in Crisis”: Contextualizing Trust Research in Emerging Business Challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Trust is essential in business operations. However, as today’s business environment is undergoing fundamental changes, trust, despite its pivotal role in buffering uncertainty and bringing forth positive changes, is considered to be “in crisis” across the globe. This is possibly due to trust research being long conducted in an acontextualized approach, leading to difficulties in addressing emerging business challenges. In response to this pressing issue in trust research, this symposium presents five interconnected lines of research seeking to contextualize trust research and address the emerging challenges organizations face. First, three papers investigate trust in three key emerging challenges: crisis, AI, and social issues. Next, two more papers investigate the flip side – feeling trusted in these emerging challenges. Together, these papers extend trust research into a variety of novel contexts to address new societal and organizational challenges. Organizational Crises and Trust in Leaders: Uncertainty Management Through Integrity Judgment Author: Eric Yuge Lou; NEOMA Business School Author: Li Huang; INSEAD Human-AI Augmentation: Is Human Oversight a Help or Hindrance in AI Management? Author: Mingyu Li; The Hong Kong University of Science and Technology Author: Thomas Bradford Bitterly; The Hong Kong University of Science and Technology Author: David Hagmann; The Hong Kong University of Science and Technology Negotiating with Anger Issues:Direction of Expressed Anger on Trust and Post-Negotiation Cooperation Author: Jonathan I Lee; University of Minnesota Duluth Author: Rachel Lea Campagna; University of New Hampshire Author: William Bottom; Washington University in St. Louis Trust in The Face of Difficult Conversations: MUM and Tough Love as Leadership Strategies Author: Emma C. E. Heine; Macquarie University Author: Elaine Hollensbe; University of Cincinnati Author: Robert C. Liden; University of Illinois at Chicago Author: Jeroen Stouten; KU Leuven A Blessing or a Curse? The Behavioral Consequences of Trust Social Comparison Author: Xiaotong (Janey) Zheng; Durham University Author: Catherine Lam; Wilfrid Laurier University Author: Xiaoyu Wang; Tongji University Author: Jingzhou Pan; Tianjin University Author: Bart De Jong; Durham University
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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 | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it