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Record W4389641513 · doi:10.34190/ecrm.21.1.162

Psychoanalytical Approach to Management Research:

2022· article· en· W4389641513 on OpenAlexaff
Evandro Bocatto, Eloísa Pérez-de-Toledo

Bibliographic record

VenueEuropean Conference on Research Methodology for Business and Management Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsMacEwan University
Fundersnot available
KeywordsUnconscious mindIrrationalityIrrational numberMetapsychologyAction (physics)PsychologyFeelingEpistemologyRationalitySocial psychologyCognitive sciencePsychoanalytic theoryPsychoanalysisPhilosophy

Abstract

fetched live from OpenAlex

Karl Popper has locked the reasoning of many researchers on a particular kind of rational thinking, that is, hypotheses stating and testing. For this reason, social sciences started to privilege a specific theory of personality. It is accurate to state that the common-sense knowledge, and resultant human "irrational" action, can be explained and even confronted by testing its assumptions. Nevertheless, Popper's categorization is not the only one possible. It neglects the irrationality of unconscious' intentions, a competing drive that directs human actions. In this paper, we discuss that, in accordance, management research and practice have strict relations with theories of personality that neglect the unconscious. For that reason, it assumes that humans are self-interested organisms like guinea pigs, neglecting this complementary supposition: the unconscious's intentions, structure, and dynamics that also drive human behavior, thinking, feeling, perceiving, and learning. The crucial integration of objective knowledge with the unconscious dynamic supposes the addition of the psychoanalytical problem to Popperian's psychological problem. Thus, the derivate capacity to explain human and social action understood as intention, plan, and act must consider conscious and unconscious intentions. The psychoanalytical approach to management research also provides ingenious methods like the awareness-enhancing interviews we present.

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)0.019
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.832
GPT teacher head0.619
Teacher spread0.212 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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