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Record W3046718477 · doi:10.1108/cdi-09-2019-0232

Career success in academia

2020· article· en· W3046718477 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCareer Development International · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOriginalityCompetence (human resources)Public relationsExploitValue (mathematics)PsychologySociologyPolitical scienceSocial psychologyCreativity

Abstract

fetched live from OpenAlex

Purpose In this study, the authors explore the boundaryless careers of faculty and adopt the intelligent career framework to examine success factors for academic careers. Design/methodology/approach The authors conducted a field study of 36 researchers in the management information systems field from 22 institutions in the US, Australia and Canada. The authors selected the participants representing four strata of researchers: luminaries (high expertise status and high citizenship behavior), experts (high expertise status but low leadership roles), statesmen (low expertise status but high leadership) and journeymen (low expertise status and low leadership). Data regarding the participants' experience of social relationships and social resources as well as entrepreneurial motivations were collected and analyzed. Findings Results show that faculty who “know-why”, “know-how”, and “know with whom” possess socially valued resources and are successful in advancing their careers. They establish high social status and exercise power within their networks to mobilize resources that promote their careers. On the other hand, faculty who fall short of these competencies impose social closure on themselves and do not strive to exploit resources available through their contacts. The study advances a number of theoretical propositions to guide future research on boundaryless intelligent careers. Social implications Social relationships and social resources do not substitute individual competence, leadership and entrepreneurial motivations; individuals need to develop competence valued by their professional communities and exploit available opportunities and assume leadership roles in order to effectively establish instrumental relationships and mobilize social resources to achieve career advancement. Originality/value In this study, we attempt to extend career development research through an examination of the bidirectional relationship between know-why, know-how and know-who in academia.

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.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.099
GPT teacher head0.357
Teacher spread0.258 · 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