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Record W6893040370 · doi:10.5281/zenodo.14166627

ACCOMPLISHMENT OF INTERORGANIZATIONAL COLLABORATION: AN ETHNOMETHODOLOGICAL STUDY OF THE COMMUNICATIVE PRACTICES OF AN INTERNATIONAL BODY

2023· dissertation· en· W6893040370 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsEthnomethodologyConstitutionSocial dialogueConversation analysisTactDiscourse analysisMultimodality

Abstract

fetched live from OpenAlex

This study looks into the communicative practices of an international body in the accomplishment of interorganizational collaboration or IOC. It aligns with the Montreal School of the communicative constitution of organization or CCO approach, wherein conversations reflect the collective experience of individual members and become authored into text that shapes the collective organization. An ethnomethodological approach was used in carrying out the data collection and analysis. This includes transcribing and coding conversations from meeting workshops of a consortium established by the Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA). Results from this study show that contextualizing, consensus building, and confirming commitment (3Cs) are accomplished through communicative practices. These 3Cs constitute IOC through co-orientation and formation of authoritative text. The 3Cs demonstrate an authoritative text that enables individual members of an interorganizational network to act in consonance as a collective organization. This study also explains how the 3Cs could help gain a better appreciation for communication as well as recommendations for future research.

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)0.013
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.013
Scholarly communication0.0070.008
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.305
GPT teacher head0.553
Teacher spread0.247 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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