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Record W7008840542

Dark future at work : scale adaptation and validation

2024· article· en· W7008840542 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

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2024
Typearticle
Languageen
FieldPsychology
TopicTechnostress in Professional Settings
Canadian institutionsGreenfield Research (Canada)
Fundersnot available
KeywordsScale (ratio)Work (physics)Adaptation (eye)Measure (data warehouse)Context (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Research on Time Perspectives dates back over 70 years, playing an integral role in clinical psychology, encapsulating how the individual views and evaluates their life.Future Time Perspectives are a critical part of clinical psychology as how the individual evaluates their future can substantially affect individual mental health.Despite this, application of this topic to the workplace has been extremely limited with Occupational Future Time Perspectives (OFTP's) specifically being a sparsely studied topic.In an attempt to bridge this gap, I created an adapted version of The Dark Future scale (Zaleski et al., 2019), attempting to measure highly negative OFTP's through the "Dark Future at Work".Results show a 2-factor structure, comprising Future Job Anxiety, and Fear of Failure at work.Initial outcomes of the Dark Future at Work scale show positive relationships with measures of depression, State/Trait Hopelessness, Burnout, Turnover Intentions, and Work Neglect/Partial Absenteeism.Contrary to predictions, perceived organizational support did not moderate these associations.Finally, theoretical applications of the scale, as well as limitations and future research directions are discussed.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.219
Teacher spread0.208 · 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