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Organization Designs for Better Healthcare: Structure and Attentional Processes in Hospitals

2020· article· en· W3046195630 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademy of Management Proceedings · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCompetitive and Knowledge Intelligence
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsOrganizational architectureHealth careOrganizational structurePsychologyCognitionContext (archaeology)Cognitive psychologyEmpirical researchKnowledge managementPublic relationsComputer sciencePolitical scienceManagementEconomics

Abstract

fetched live from OpenAlex

A long tradition of research recognizes that organization design choices plays a key role in orchestrating the information processing of the firm and hence in the outcomes that follow. Reflected in this research is a growing interest in the cognitive consequences associated with variations in organization structure. Yet our understanding of the relationship between organizational structures and its attentional properties is not well established. This is a major shortcoming given that organizations face an ever-increasing need to balance the complexity of competing with often contradictory attentional demands amidst an increasing need for faster learning, greater efficiencies, and better performance. Our symposium addresses both the theoretical and empirical gaps in our understanding of organization design and attention in the context of hospitals, where the attentional demands and the need for better decision making is large. The three empirical papers that will be presented examine the relationship between structure, attentional processes, and organizational behavior in hospitals. They also open up new avenues of research for scholars interested in organization design, attention, and/or healthcare. In addition, a discussion will be led by William Ocasio (Northwestern University), who will utilize the attention-based view of the firm to outline a research agenda for studying the coupling and decoupling of governance and operational channels - both formal and informal - in hospitals, and the consequences for the resulting structural distribution of organizational attention. The Complexity of Environmental and Task Attentional Demands for Hospitals Presenter: William Ocasio; Northwestern U. Information Processing, Attentional Engagement, and Organizational Structure Presenter: John Joseph; U. of California, Irvine Presenter: Alex James Wilson; U. of Minnesota Presenter: Jay (Jinwon) Park; U. of California, Irvine Redesigning an Organization’s Microgeography Presenter: Jillian Chown; Northwestern Kellogg School of Management Presenter: Christopher C. Liu; U. of Oregon Do Individuals Learn Differently from Senior Versus Junior Colleagues’ Failures in Organizations? Presenter: Sunkee Lee; Carnegie Mellon U. - Tepper School of Business Presenter: Jisoo Park; Carnegie Mellon U. - Tepper School of Business

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.555

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 communication0.0000.001
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 head0.032
GPT teacher head0.261
Teacher spread0.229 · 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