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Ambition in Organizational Life: What the Heck Are We Talking About?

2019· article· en· W2966160807 on OpenAlexaff
Masoud Shadnam, Charles Keim

Bibliographic record

VenueAcademy of Management Proceedings · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMacEwan University
Fundersnot available
KeywordsSituatedOrganization studiesMeaning (existential)Set (abstract data type)ConstellationSociologyCurrencyPublic relationsEpistemologyGrounded theoryPolitical scienceQualitative researchSocial scienceComputer scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

The term ambition and its derivatives, such as ambitions, ambitious, and unambitious, constitute a commonly-used set of signifiers in business and managerial discourses. Despite this wide currency in the discourses of business professionals and practitioner-oriented publications, management researchers to date have not sought to understand ambition and the various ways that it figures in business discourses. In this paper, we take an interpretive, grounded theory approach to explore the intricate meanings and workings of the notion of ambition in three top-ranked practitioner-oriented business journals from 2010 to 2018. Our findings show that there are four different constellations of meaning that surround ambition. We identify and draw out the specifications of these constellations, which sheds light on how ambition is situated in different communicative contexts and connected with different regimes of managerial prescription. We conclude with a discussion of the implications of these findings for management and organization studies.

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)0.011
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0100.058
Scholarly communication0.0230.019
Open science0.0010.007
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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