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Record W2028098149 · doi:10.1080/01580370802097702

Partnering for research: A critical discourse analysis

2008· article· en· W2028098149 on OpenAlexaff
Catherine Irving, Leona M. English

Bibliographic record

VenueStudies in Continuing Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsGeneral partnershipPhenomenonAffect (linguistics)Power (physics)SociologyCritical theoryCritical discourse analysisProcess (computing)Social PartnershipPedagogyDiscourse analysisPublic relationsEpistemologyEngineering ethicsPolitical sciencePublic administrationEngineeringLinguisticsComputer scienceLawPolitics

Abstract

fetched live from OpenAlex

Using a critical discourse analysis, informed by poststructuralist theory, we explore the research phenomenon of coerced partnership. This lens allows us to pay attention to the social relations of power operating in knowledge generation processes, especially as they affect feminist researchers in adult education. We propose an alternative vision of partnership which politicizes the term partnership, attends to civil society, maps resistances and values the process by all partners.

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)0.069
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.010
Science and technology studies0.0150.028
Scholarly communication0.0180.021
Open science0.0030.011
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.561
GPT teacher head0.661
Teacher spread0.100 · 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 designQualitative
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

Citations17
Published2008
Admission routes1
Has abstractyes

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