Dancing the two-step: Collaborating with intermediary organizations as research partners to help implement workplace health and safety interventions
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
OBJECTIVE: To evaluate the effect of the involvement of intermediaries who were research partners on three intervention studies. The projects crossed four sectors: manufacturing, transportation, service sector, and electrical-utilities sectors. The interventions were participative ergonomic programs. The study attempts to further our understanding of collaborative workplace-based research between researchers and intermediary organizations; to analyze this collaboration in terms of knowledge transfer; and to further our understanding of the successes and challenges with such a process. PARTICIPANTS: The intermediary organizations were provincial health and safety associations (HSAs). They have workplaces as their clients and acted as direct links between the researchers and workplaces. METHODS: Data was collected from observations, emails, research-meeting minutes, and 36 qualitative interviews. Interviewees were managers, and consultants from the collaborating associations, 17 company representatives and seven researchers. RESULTS: The article describes how the collaborations were created, the structure of the partnerships, the difficulties, the benefits, and challenges to both the researchers and intermediaries. The evidence of knowledge utilization between the researchers and HSAs was tracked as a proxy-measure of impact of this collaborative method, also called Mode 2 research. CONCLUSION: Despite the difficulties, both the researchers and the health and safety specialists agreed that the results of the research made the process worthwhile.
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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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