MétaCan
Menu
Back to cohort
Record W2089907250 · doi:10.1177/1086026612475069

The Time and Space of Materiality in Organizations and the Natural Environment

2013· article· en· W2089907250 on OpenAlexafffund
Pratima Bansal, Janelle Knox‐Hayes

Bibliographic record

VenueOrganization & Environment · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of CanadaCenter for Global Partnership
KeywordsMateriality (auditing)Futures contractNatural capitalSpace (punctuation)SociologyBusinessEconomicsComputer scienceAestheticsFinancial economicsEcologyArt

Abstract

fetched live from OpenAlex

In this article, we argue that prior organizations research has contributed to the erosion of the natural environment by failing to discriminate physical materiality from sociomateriality. The time–space attributes of physical materiality are more immutable than sociomateriality, so the compression of time and space in and by organizations is disrupting the cycles of the natural environment. We illustrate this point through the example of carbon markets. The development of futures and other financial derivatives contributes to the compression of time, whereas the movement of capital worldwide contributes to the compression of space. This time–space compression disembodies financial instruments from their physical target, namely, carbon, leading to the distortion of the instrument’s “real” value and hampering carbon emissions reductions. We call for organizational theories that more fully account for physical materiality.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.009
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.046
Scholarly communication0.0090.012
Open science0.0010.006
Research integrity0.0020.002
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 head0.002
GPT teacher head0.140
Teacher spread0.138 · 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

Citations145
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueOrganization & EnvironmentSame topicManagement and Organizational StudiesFrench-language works237,207