Dark future at work : scale adaptation and validation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".