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Record W4226493564 · doi:10.1177/00218863221090305

Unpacking “Sense of Place” and “Place-making” in Organization Studies: A Toolkit for Place-sensitive Research

2022· article· en· W4226493564 on OpenAlexaff
Mélodie Cartel, Ewald Kibler, M. Tina Dacin

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSense of placeUnpackingSociologyScholarshipPhenomenology (philosophy)Relation (database)Set (abstract data type)EpistemologySocial scienceComputer sciencePolitical science

Abstract

fetched live from OpenAlex

There is increasing interest in organizational scholarship in the role of place. To support these developments, we offer a framework for place-sensitive research in organizational analysis. The notion of place refers to a unique location, endowed with a material from and a socially constructed set of meanings. In line with the phenomenology of place, our framework first distinguishes between two ontologies of place: place as experience—through which people develop a sense of place—and place as practice—through which people engage collectively to make places. Second, our framework distinguishes between three temporal orientations in relation to place: past, present, and future. We then draw from research in geography to reflect on two under-explored methodological toolkits to collect data on and analyze place as experience and place as practice in organization studies: walking interviews, and geographical videography.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.062
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.938
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.044
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0170.013
Science and technology studies0.0140.147
Scholarly communication0.0300.052
Open science0.0060.033
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0040.001

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 head0.089
GPT teacher head0.357
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations53
Published2022
Admission routes1
Has abstractyes

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