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Situated Institutions: The Role of Place, Space and Embeddedness in Institutional Dynamics

2018· article· en· W2823273432 on OpenAlexaboutno aff
Tina Dacin, Tammar B. Zilber, Michael Lounsbury

Bibliographic record

VenueAcademy of Management Proceedings · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsWrightSociologySituatedEmbeddednessPolitical scienceMedia studiesSocial scienceHistoryArt history

Abstract

fetched live from OpenAlex

Place and space have long been the focus of studies of organizations (e.g. Bucher & Langley, 2016; Elsbach, 2004; Elsbach & Pratt, 2007; Tuan, 1974), but only recently were explored, mostly indirectly, in institutional studies. For example, recent work examines the role of place in institutional change on the organizational (Kellogg, 2009), community (Marquis & Battilana, 2009), field (Lounsbury, 2007; Ziestma & Lawrence, 2010), or societal levels (Mair, 2012). Recent studies also explore the role of place in institutional work (Lawrence & Dover, 2015) and in reviving tradition (Dacin, Nasra, & Leithwood, 2009). Our symposium explores the situatedness of institutional dynamics. Through the presentation of four empirical studies, we will discuss how place impacts the salience, resonance, strength and scope of institutions. With an introduction to place at the beginning, discussant’s comments and a directed Q&A with audience participation at the end, this symposium will also explore the value of place to broader discussions about institutions. Exactly Your Grandpas Shoes: Historical Legacies of Place in Revitalizing a Decimated Industry Presenter: Sunasir Dutta; U. of Minnesota Presenter: Michael Park; U. of Minnesota Know Thy Place: Location and Imagined Communities in Institutional Field Dynamics Presenter: Tammar B. Zilber; Hebrew U. of Jerusalem Institutional Vigilantism and the Protection of Place Presenter: Brett Crawford; Purdue U. Presenter: Tina Dacin; Queen's U. Maintaining Places of Social Inclusion: Ebola and the Emergency Department Presenter: April L. Wright; U. of Queensland Presenter: Alan D. Meyer; U. of Oregon Presenter: Trish Reay; U. of Alberta

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.315
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 designTheoretical or conceptual
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

Citations2
Published2018
Admission routes1
Has abstractyes

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