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Change, Loss, and Grief in Organizations

2025· article· en· W4416000527 on OpenAlexaffabout
F Katelynn Boland, Elizabeth E. Stillwell, Shoshana Dobrow Riza, Shannon Leigh Sciarappa, Jayci Robison Pickering, Elizabeth Sheprow, Alexandra Feldberg, Daniel J. Chiacchia, Rachel Lise Ruttan, Katherine A. DeCelles, Sora Jun, George Newman

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGriefScholarshipCoping (psychology)Mental healthCognitive reframingWork (physics)

Abstract

fetched live from OpenAlex

This symposium, titled “Change, Loss, and Grief in Organizations,” explores the multifaceted impact of change, loss, and grief on employees and organizations. Change, loss, and grief—whether personal or professional—are universal experiences that shape the work-life interface. However, organizational scholarship has only begun to unpack the complex ways these experiences influence individuals and workplaces. This symposium advances understanding by examining the varied and nuanced ways individuals process both personal and professional change, loss, and grief, including how these processes affect communication, sense-making, and recovery; and strategies organizations, leaders, and colleagues can adopt to effectively support those navigating these experiences and emotions. Bringing together diverse methodological approaches—mixed methods, qualitative, and quantitative—this symposium highlights innovative perspectives on how employees experience, cope with, and adapt to change, loss, and grief in the workplace. Research-based insights from these papers aim to inform organizational policies and practices that foster resilience, compassion, and well-being. The symposium seeks to engage scholars interested in change, loss, and grief, while offering actionable recommendations for future research and practice. Understanding Loss: How Experiences of Loss and Coping Strategies Impact Wellbeing Author: F Katelynn Boland; Answered and Abandoned: Navigating Meaningfulness and Mental Health After Abandoning a Calling Author: Shannon Leigh Sciarappa; Boston College In for the Long Haul: How Long COVID and Loss of Self Shape Identity, Well-being, and Work Author: Elizabeth E. Stillwell; The London School of Economics & Political Science Author: Jayci Robison Pickering; When Loss Bleeds into Work Life: How Workers Manage Disenfranchised Grief Author: Elizabeth Sheprow; Harvard Business School Author: Alexandra Feldberg; Harvard Business School Why Grit Doesn’t Work For Grief Author: Daniel J. Chiacchia; University of Toronto Author: Rachel Lise Ruttan; University of Toronto Author: Katherine Ann DeCelles; University of Toronto Author: Sora Jun; Rice University Author: George Newman; University of Toronto

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.314
Teacher spread0.290 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes2
Has abstractyes

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