Organizational Collaborative Capacities in Disaster Management: Evidence from the Taiwan Red Cross Organization
Bibliographic record
Abstract
In the post disaster situation, relief organizations are expected to learn and adjust their capacity to collaborate with other major players such as nonprofit organizations, government agencies, and local workers. In other words, effective responses to disasters require capacity for collaboration on the part of emergency response agencies; however in disaster affected area, not every relief organization is equally capable of doing so. The capacity for organizations to collaborate with others in and after a disaster does not occur spontaneously or in a vacuum. Since organizational collaborative capacity is essential in disaster relief, it is imperative to present empirical evidence regarding organizational collaborative capacity. The purpose of this paper is to develop a working theory of what characteristics an emergency response organization needs in order to develop collaborative capacity. We analyze collaborative capacities by examining two events: the 2004 Asian Tsunami and the 2008 Wenchuan Earthquake. This piece argues that collaborative capacity, defined by purpose, structure communication and resources, is a requisite for collaboration in a post disaster situation. The implications for practitioners and scholars in post disaster society 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.
How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".