Beyond feedback: understanding how feedforward can support employee development
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.
Bibliographic record
Abstract
Purpose Recent research has found that a technique called feedforward interviewing (FFI) can be used to develop employees on the job. Currently the mechanisms and boundary conditions of the FFI-performance relationship are unexplored. Using a positive psychology framework, the purpose of this paper is to discuss how FFI supports the creation of personal and relational resources, and explores the contextual and environmental limits to the effectiveness of the technique. Design/methodology/approach Through a review of the literature as well as examination through appropriate theoretical lenses, moderators of FFI are proposed and the implications for the effectiveness of the technique are examined. Findings The FFI model explored in this paper is rooted in broaden and build theory as well as other theories from the positive psychology literature. Design recommendations and future research directions are discussed. Originality/value Through a scholarly review of the literature, the potential for the effective use of a new developmental technique is explored. Direct guidance on how to apply FFI in organizations is given.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it