What we’ve got here is a failure to communicate: HRM signal, lenses and refraction at Nav Canada in crisis
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 To analyse the HRM response to the coronavirus disease 2019 (COVID-19) pandemic by an organisation severely affected by the subsequent crisis, i.e. Nav Canada. Design/methodology/approach The paper draws on data from a large-scale study of air navigation service providers and presents a case study of Nav Canada that is comprised of interviews, focus groups and secondary source data analysis. Findings Several lenses through which the HRM signal passes are identified that are used by the trade union to refract the HRM signal before relaying it both to stakeholders within the organisation, i.e. its members, and to stakeholders beyond the organisation, in this case, the general public and the Canadian government. Research limitations/implications Future research might explore the degree to which lenses amplify or refract the HRM signal, assessing which is most effective to ensure amplification and avoid refraction and under what conditions. Research that assesses the comparative efficacy of temporal versus among group (in)consistency or in HRM policies and HRM processes (and in particular the employment relations climate) in forming lenses is especially welcome. Longitudinal studies that explore the attitudes of workers to the HRM signal over time, explaining why changes in attitudes are observed, will be highly instructive. Practical implications The study reveals the dangers of responding to crises with alacrity and without the cooperation and buy-in (or consensus) among workers and their trade unions. Where difficult decisions have to be made, the manner in which they are made is an important influence on how trade unions and employees are likely to respond. Originality/value The HRM system strength model and HRM signalling theory are advanced via the application of the lens metaphor, by which it is possible to include aspects of the broader employment relationship that are often omitted from mainstream HRM analysis. The paper also explains the role of the trade union in the HRM signalling process.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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