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Record W4307649982 · doi:10.1002/cdq.12306

Temporality: A fruitful concept for understanding, studying, and supporting people in transition

2022· article· en· W4307649982 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.

Bibliographic record

VenueThe Career Development Quarterly · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTemporalityTransition (genetics)Anticipation (artificial intelligence)EpistemologyMeaning (existential)SociologyPsychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The specific processes of transitions or turning points have been studied in different fields, notably vocational psychology, career development, sociology, and the life‐course approach. However, little work has brought together these different strands of research. To fill this gap, we explore the issue of temporality, raised to varying degrees by each approach, with the aim of showing its heuristic value in the study of career transitions. After clarifying a number of concepts, we describe research methodologies that can be used to identify temporality and suggest keys of comprehension to understand transitions from a temporal angle. Finally, we describe intervention avenues that take temporality into account to support people in career transition. Covering the past, the present, and the future, they aim to stimulate self‐reflection in order to give meaning to the most significant biographical experiences and, hence, make the present clearer and anticipation of the future easier.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.086
GPT teacher head0.289
Teacher spread0.203 · 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