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Record W2142114233 · doi:10.1177/1059601112443850

The Treatment of the Relationship Between Groups and Their Environments

2012· article· en· W2142114233 on OpenAlexaff
Maryam Kouchaki, Gerardo A. Okhuysen, Mary J. Waller, Golnaz Tajeddin

Bibliographic record

VenueGroup & Organization Management · 2012
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsYork University
Fundersnot available
KeywordsExtant taxonField (mathematics)PsychologyResource (disambiguation)Key (lock)Social psychologyComputer scienceEcologyMathematicsBiology

Abstract

fetched live from OpenAlex

Despite the recognized importance of groups’ external contexts to their functioning, there is little research that fully explicates the relationship between groups and their environments. Instead, much extant research treats groups as closed systems. To advance the field’s understanding, we explore the treatment of the relationship between groups and their environments in existing literature by reviewing research that incorporates groups in naturally varying environments. We identify three predominant characterizations in the literature: the environment as a resource pool, as an impetus for change, and as a target. We offer a summary of the assumptions in these characterizations, a critical examination of each characterization, and develop a future research agenda that extends each characterization and challenges its key assumptions in an effort to explore the relationship between groups and their external environments.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0060.032
Scholarly communication0.0100.009
Open science0.0030.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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.

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

Citations26
Published2012
Admission routes1
Has abstractyes

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