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Record W2159146811 · doi:10.1177/0018726700539006

Discourse as a Strategic Resource

2000· article· en· W2159146811 on OpenAlexaff
Cynthia Hardy, Ian Palmer, Nelson Phillips

Bibliographic record

VenueHuman Relations · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsNarrativePerformativitySociologyResource (disambiguation)Meaning (existential)EpistemologySubject (documents)Position (finance)LinguisticsComputer scienceGender studiesBusiness

Abstract

fetched live from OpenAlex

In this article, we outline a model of how discourse can be mobilized as a strategic resource. The model consists of three circuits. First, in circuits of activity, individuals attempt to introduce new discursive statements, through the use of symbols, narratives, metaphors, etc. aimed at evoking concepts to create particular objects. These activities must intersect with circuits of performativity. This occurs when, for example, concepts are contextually embedded and have meaning for other actors; when symbols, narratives and metaphors possess receptivity; and when the subject position of the enunciator warrants voice. Third, when these two circuits intersect, connectivity occurs as the new discursive statements `take'. Using an illustrative example of an international NGO operating in Palestine, we show how an individual brought about strategic change by engaging in discursive activity.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.017
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0070.031
Scholarly communication0.0170.025
Open science0.0030.011
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0150.003

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 head0.026
GPT teacher head0.251
Teacher spread0.225 · 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

Citations585
Published2000
Admission routes1
Has abstractyes

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