| Nov. 27, 2023, 2:14 p.m. |
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{"external_links": []}
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| Nov. 20, 2023, 2:04 p.m. |
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{"external_links": []}
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| Nov. 13, 2023, 1:34 p.m. |
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{"external_links": []}
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| Nov. 6, 2023, 1:32 p.m. |
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{"external_links": []}
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| Aug. 14, 2023, 1:31 p.m. |
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{"external_links": []}
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| Aug. 7, 2023, 1:32 p.m. |
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{"external_links": []}
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| July 31, 2023, 1:35 p.m. |
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| July 24, 2023, 1:36 p.m. |
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{"external_links": []}
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| July 17, 2023, 1:35 p.m. |
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| July 10, 2023, 1:26 p.m. |
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| July 3, 2023, 1:27 p.m. |
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| June 26, 2023, 1:26 p.m. |
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{"external_links": []}
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| June 19, 2023, 1:27 p.m. |
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{"external_links": []}
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| June 12, 2023, 1:30 p.m. |
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{"external_links": []}
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| June 5, 2023, 1:34 p.m. |
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{"external_links": []}
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{"external_links": []}
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| May 22, 2023, 1:29 p.m. |
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{"external_links": []}
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| May 15, 2023, 1:32 p.m. |
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{"external_links": []}
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| May 8, 2023, 1:38 p.m. |
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{"external_links": []}
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| May 1, 2023, 1:28 p.m. |
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{"external_links": []}
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| April 24, 2023, 1:35 p.m. |
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{"external_links": []}
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| April 17, 2023, 1:28 p.m. |
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| April 10, 2023, 1:25 p.m. |
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| April 3, 2023, 1:27 p.m. |
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{"external_links": []}
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| Jan. 28, 2023, 11:09 a.m. |
Created
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[{"model": "core.projectfund", "pk": 31197, "fields": {"project": 8423, "organisation": 4, "amount": 49747, "start_date": "2022-11-01", "end_date": "2023-03-30", "raw_data": 39937}}]
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| Jan. 28, 2023, 11:09 a.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 88702, "fields": {"project": 8423, "organisation": 10134, "role": "PARTICIPANT_ORG"}}]
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| Jan. 28, 2023, 11:09 a.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 88701, "fields": {"project": 8423, "organisation": 10134, "role": "LEAD_ORG"}}]
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| Jan. 28, 2023, 11:09 a.m. |
Created
40
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[{"model": "core.projectperson", "pk": 55559, "fields": {"project": 8423, "person": 11861, "role": "PM_PER"}}]
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| Jan. 28, 2023, 10:52 a.m. |
Updated
35
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{"title": ["", "Re:Hatch"], "description": ["", "\nAs we transition to a low carbon, zero-emission future, the decisions we make around transport will play a critical role. Re:Hatch is an innovative R&D project that aims to use artificial intelligence and machine learning to help develop a digital solution to optimise transport.\n\nPeople and businesses require better, more relevant information to help them cut through industry noise, automotive rhetoric and public misconceptions. Appropriate and engaging tools will be necessary to help people respond promptly and responsibly to the climate emergency. Behavioural change is traditionally a slow and challenging task. Through utilising technology in an innovative way, Rerwt aims to bridge the knowledge gap and speed up the time it takes for people to move away from damaging and unhealthy transport choices. Organisations will benefit from a data-drive consultancy service encapsulating statutory emission reporting, sustainable planning and organisational mobility support.\n\nAs Rerwt scales, local, regional and national learnings will support broader, longer-term policy, energy and infrastructure planning.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Active"]}
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| Jan. 28, 2023, 10:52 a.m. |
Added
35
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{"external_links": [34447]}
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| Jan. 28, 2023, 10:52 a.m. |
Created
35
|
[{"model": "core.project", "pk": 8423, "fields": {"owner": null, "is_locked": false, "coped_id": "56bf3aa2-af62-4461-baa7-8d2a06d01ce9", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 39922, "created": "2023-01-28T10:48:47.621Z", "modified": "2023-01-28T10:48:47.621Z", "external_links": []}}]
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