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Record W2057658825 · doi:10.1108/17465641111129362

Subjective personal introspection in action‐oriented research

2011· article· en· W2057658825 on OpenAlexaff
Michel Rod

Bibliographic record

VenueQualitative Research in Organizations and Management An International Journal · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsIntrospectionOriginalityReflexivityAction (physics)Context (archaeology)Action researchQualitative researchSociologyPublic relationsPsychologyEngineering ethicsPolitical scienceSocial scienceEngineeringCognitive psychologyPedagogy

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to describe the rationale and use of subjective personal introspection (SPI) as a methodological approach. Design/methodology/approach SPI was utilised to develop a “narrative” of the author's own “action‐oriented” research experience within a multisector collaborative venture established by 13 partner organisations representing the academic, pharmaceutical industry and government sectors. The “confessional” stance that the study assumes describes some of the perceived tensions enacted during field work. The SPI approach is theoretical and reflective, as well as descriptive and analytical, in reporting the antecedents, actions, and outcomes in action‐oriented research. Findings Because the focus of the paper is subjective, personal, and introspective, it does not illustrate “findings” about multisector collaboration, but rather reflections and insights about the way the research was conducted. Practical implications The paper widens the forum for incorporating SPI beyond the consumer behaviour context to the context in which action‐oriented researchers incorporate introspection in their study of organisations. Originality/value The paper goes some way to bridging the gap between SPI and reflexivity (if there is indeed a gap) and it causes qualitative, action‐oriented organisational researchers to contemplate a number of questions: what is the role of the researcher; what is the source of their authority to narrate and what are they authorised to recount; and what are the consequences of this?

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0000.001
Research integrity0.0000.001
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 head0.232
GPT teacher head0.479
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 teacher head, not a consensus.

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

Citations29
Published2011
Admission routes1
Has abstractyes

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