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Institutional Ethnography, Critical Discourse Analysis, and the Discursive Coordination of Organizational Activity

2017· book-chapter· en· W2766294013 on OpenAlexaboutno aff
David Peacock

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCritical discourse analysisAppropriationSociologyDiscourse analysisCritical ethnographyPublic relationsEthnographyMedia studiesPolitical scienceEpistemologyIdeologyPoliticsLinguisticsLaw

Abstract

fetched live from OpenAlex

Abstract Institutional ethnography (IE) is a social ontology pioneered by Dorothy Smith, the Canadian feminist-sociologist. Conceptualizing discourse as social relations that are organized by the activities of people and are empirically investigable, IE has been increasingly employed by researchers outside of sociology in fields such as education and health. The goal in these cases has often been to explicate the effects of power flowing through textually mediated discourses that work to reconfigure local practices to align with official policy mandates. Yet the discourse analysis performed in much IE to date has not paid close linguistic attention to the way specific actors utilize texts in an active appropriation of what Smith calls the “ruling relations” constituting official discourses. Using data from an IE of student equity practices in Australian higher education, this chapter illustrates how a Fairclough-inspired critical discourse analysis (CDA) of the “orders of discourse” assembled within a relay of university and government texts is able to provide useful analytical purchase on how equity policies are actively appropriated within a university outreach practice. It demonstrates how the accomplishment of student equity outreach involves the hybridizing of equity and excellence discourses in ways that bolster the dominant position of an Australian university. This working together of distinct IE and CDA approaches offers possibilities for more nuanced accounts of individual and collective agency in the process of semiotic and social change.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.010
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.299
Teacher spread0.275 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations8
Published2017
Admission routes1
Has abstractyes

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