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Paper Citation Record · LEDGER

LegiGPT: Party Politics and Transport Policy with Large Language Model

As of 14 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2506.16692.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.16692 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:42:13.975230Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy30
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 49b98a62-8b1e-4222-ac8e-ec4db4e9ccda · outbound

This paper cites Political competition, party polarization, and government performance.Public Choice, 161:427–450, 2014.

LegiGPT: Party Politics and Transport Policy with Large Language Model Political competition, party polarization, and government performance.Public Choice, 161:427–450, 2014

Reference 1

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Observation f6672c63-8e9d-43e3-8590-041e75e64865 · outbound

This paper cites Conservatives and progressives in south korea.

LegiGPT: Party Politics and Transport Policy with Large Language Model Conservatives and progressives in south korea

Reference 2

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Observation fcb6fe64-e105-422f-b760-a4bb847b897e · outbound

This paper cites an unresolved cited work.

LegiGPT: Party Politics and Transport Policy with Large Language Model Unresolved cited work

Reference 3

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Observation 1dfa496d-4207-498a-becb-1f892dee3972 · outbound

This paper cites Political partisanship and transportation reform.

LegiGPT: Party Politics and Transport Policy with Large Language Model Political partisanship and transportation reform

Reference 4

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.519024Z digest=sha256:437425865277b18992eb9b7dad631b4a177b95835f2a0dde8c470b26c387d91f

Observation 105aace0-f847-431c-a1a9-08e807e5ab19 · outbound

This paper cites Consensus planning in transport: The case of vancouver’s transportation plebiscite.

LegiGPT: Party Politics and Transport Policy with Large Language Model Consensus planning in transport: The case of vancouver’s transportation plebiscite

Reference 5

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source=pdf_text observed=2026-08-06T23:42:13.617036Z digest=sha256:31bfac8d23fa7a07f594d2c1fb4d3ed6650e729feaa9e61057dc556f30e96cc2

Observation d16fd771-64ee-438a-9930-b7d34000ce45 · outbound

This paper cites The politics of collective public participation in transportation decision-making.

LegiGPT: Party Politics and Transport Policy with Large Language Model The politics of collective public participation in transportation decision-making

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.643945Z digest=sha256:e75d8952f1eb8db9680d6985feaad04bc41293c8554f0d8c036d18a7f170a209

Observation 517e06d6-88d6-4e5f-a641-5e40af2b889d · outbound

This paper cites State legislator views on funding 21st century transportation: Important problems, missed connections.Transport Policy, 150:206– 218, 2024.

LegiGPT: Party Politics and Transport Policy with Large Language Model State legislator views on funding 21st century transportation: Important problems, missed connections.Transport Policy, 150:206– 218, 2024

Reference 7

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source=pdf_text observed=2026-08-06T23:42:13.648413Z digest=sha256:7657bccb5a380ff8eb9d016d7628100e652c4c393b381a5137b264ddaa1cdc46

Observation 548525ed-f170-42cf-8b63-bae02834080e · outbound

This paper cites Christenson.

LegiGPT: Party Politics and Transport Policy with Large Language Model Christenson

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.652130Z digest=sha256:378fa5bbf51819d3573d1f25688d1fe79cea72be752ab58464ad948019bba4c7

Observation 33cd980e-32c9-4588-b48f-20d76c01a883 · outbound

This paper cites What does america spend on transportation and infrastructure? is infrastruc- ture improving?, 2024.

LegiGPT: Party Politics and Transport Policy with Large Language Model What does america spend on transportation and infrastructure? is infrastruc- ture improving?, 2024

Reference 9

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.658734Z digest=sha256:ebbeb3eef1a9d0df7b669944ce75700b1718f2da5c58ae9e47cef23e78707d7e

Observation 26e9f2d4-9750-42b7-b108-4d6f7c55ed79 · outbound

This paper cites Bipartisan infrastructure law (bil) / infrastructure investment and jobs act (iija), 2023.

LegiGPT: Party Politics and Transport Policy with Large Language Model Bipartisan infrastructure law (bil) / infrastructure investment and jobs act (iija), 2023

Reference 10

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source=pdf_text observed=2026-08-06T23:42:13.662412Z digest=sha256:6ef00c94edd274b935774368da4197dfd201aa23b295c6ff35886961bea775bc

Observation 24266dc4-22d4-4955-a695-2845e99648d5 · outbound

This paper cites Public support of transport policy instruments, perceived transport quality and satisfaction with democracy.

LegiGPT: Party Politics and Transport Policy with Large Language Model Public support of transport policy instruments, perceived transport quality and satisfaction with democracy

Reference 11

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source=pdf_text observed=2026-08-06T23:42:13.667033Z digest=sha256:7ec5013cf0f10b1cde648c09045a5a8ad6a74940cd676506da6e791b9cf450ac

Observation 4081de3a-0176-4200-82b8-f3195304679e · outbound

This paper cites Toward human-centric urban infrastructure: Text mining for social media data to identify the public perception of covid-19 policy in transportation hubs.

LegiGPT: Party Politics and Transport Policy with Large Language Model Toward human-centric urban infrastructure: Text mining for social media data to identify the public perception of covid-19 policy in transportation hubs

Reference 12

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source=pdf_text observed=2026-08-06T23:42:13.669916Z digest=sha256:03a4608e010a717c0f6a129d52f199de07370f887ba5194c9ffbad869af2225d

Observation 5e3b7959-d77e-435b-a69a-daa1898b36bc · outbound

This paper cites Investigation of critical factors for future-proofed trans- portation infrastructure planning using topic modeling and association rule mining.

LegiGPT: Party Politics and Transport Policy with Large Language Model Investigation of critical factors for future-proofed trans- portation infrastructure planning using topic modeling and association rule mining

Reference 13

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source=pdf_text observed=2026-08-06T23:42:13.673332Z digest=sha256:d9a270a65eea2da9429ad247b6c2e5d07ae4f6b5d9c3367d6afea29816ac313d

Observation cb4a3224-61c4-4c77-984d-193b8ba303b2 · outbound

This paper cites an unresolved cited work.

LegiGPT: Party Politics and Transport Policy with Large Language Model Unresolved cited work

Reference 14

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a5f9449e-d532-4c5d-aba6-a69d8cfaf633 · outbound

This paper cites Exploring the evolution trends of port integration policy in china by a text mining approach.

LegiGPT: Party Politics and Transport Policy with Large Language Model Exploring the evolution trends of port integration policy in china by a text mining approach

Reference 15

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source=pdf_text observed=2026-08-06T23:42:13.686316Z digest=sha256:ce210dd61f6765067b046099d44839783268d28c37b70919e6f64e3cea43afdf

Observation a3665957-c013-40f4-ab7b-03e7b89f7af3 · outbound

This paper cites Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies.

LegiGPT: Party Politics and Transport Policy with Large Language Model Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies

Reference 16

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local_arxiv, observed 2026-08-06T23:42:14.080192Z

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Observation 6e7a0e9a-ca0f-4e91-b02f-a130f3e957ed · outbound

This paper cites Metroberta: Leveraging traditional customer rela- tionship management data to develop a transit-topic-aware language model.

LegiGPT: Party Politics and Transport Policy with Large Language Model Metroberta: Leveraging traditional customer rela- tionship management data to develop a transit-topic-aware language model

Reference 17

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Observation 418d6e07-4f98-472b-b097-2da8bfec8f6a · outbound

This paper cites A Large Language Model for Feasible and Diverse Population Synthesis.

LegiGPT: Party Politics and Transport Policy with Large Language Model A Large Language Model for Feasible and Diverse Population Synthesis

Reference 18

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source=pdf_text observed=2026-08-06T23:42:13.704027Z digest=sha256:54dd4c3a4da1af37309a9a2f0df99b41cf3ed88022de18ba7b8146bb60cef7a1

Observation aa155f7f-1f9a-4fe3-a1d9-20c7c3a00664 · outbound

This paper cites Large language models outperform expert coders and supervised classi- fiers at annotating political social media messages.

LegiGPT: Party Politics and Transport Policy with Large Language Model Large language models outperform expert coders and supervised classi- fiers at annotating political social media messages

Reference 19

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Observation c8c6c52a-f505-48c3-bbd4-b3d13d65774c · outbound

This paper cites Linear Representations of Political Perspective Emerge in Large Language Models.

LegiGPT: Party Politics and Transport Policy with Large Language Model Linear Representations of Political Perspective Emerge in Large Language Models

Reference 20

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Observation e5576a05-1272-4932-a1ea-6e3fa1a631f8 · outbound

This paper cites an unresolved cited work.

LegiGPT: Party Politics and Transport Policy with Large Language Model Unresolved cited work

Reference 21

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Observation acadbdcf-afd3-4e6d-b2b7-49f59854ef35 · outbound

This paper cites Emergent Abilities of Large Language Models.

LegiGPT: Party Politics and Transport Policy with Large Language Model Emergent Abilities of Large Language Models

Reference 22

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source=pdf_text observed=2026-08-06T23:42:13.728260Z digest=sha256:f046809798f2b68644e3deaf2157b9d664d9fcffdc69133acfbe22c9e2b0e3bd

Observation 8821e2a7-84e2-4ef4-bf46-c2998aa7842f · outbound

This paper cites an unresolved cited work.

LegiGPT: Party Politics and Transport Policy with Large Language Model Unresolved cited work

Reference 23

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Observation 16685552-3acb-4dec-a0ff-545af35256a0 · outbound

This paper cites Zhang, D.

LegiGPT: Party Politics and Transport Policy with Large Language Model Zhang, D

Reference 24

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Observation 96915ae8-5c7e-481f-a9e7-15bbc7b8ccc6 · outbound

This paper cites Public data portal, 2024.

LegiGPT: Party Politics and Transport Policy with Large Language Model Public data portal, 2024

Reference 25

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Observation 730f1750-72ae-4b94-bb0c-12c3803c298d · outbound

This paper cites Could We Have Had Better Multilingual LLMs If English Was Not the Central Language?.

LegiGPT: Party Politics and Transport Policy with Large Language Model Could We Have Had Better Multilingual LLMs If English Was Not the Central Language?

Reference 26

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Observation 993ddb25-7dd8-444e-861b-abd505b6e0cb · outbound

This paper cites A unified approach to interpreting model predictions.

LegiGPT: Party Politics and Transport Policy with Large Language Model A unified approach to interpreting model predictions

Reference 27

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Observation 9e5bfbea-9c41-42f6-84b9-e23011652696 · outbound

This paper cites Deep multimodal learning for traffic speed estimation combining dedicated short-range communication and vehicle detection system data.

LegiGPT: Party Politics and Transport Policy with Large Language Model Deep multimodal learning for traffic speed estimation combining dedicated short-range communication and vehicle detection system data

Reference 28

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 83cf21f2-d219-489e-af9b-31f187b40591 · outbound

This paper cites Mlp- mixer: An all-mlp architecture for vision.

LegiGPT: Party Politics and Transport Policy with Large Language Model Mlp- mixer: An all-mlp architecture for vision

Reference 29

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation afca219c-689c-483e-992a-747c5379d9e7 · outbound

This paper cites Random forests.

LegiGPT: Party Politics and Transport Policy with Large Language Model Random forests

Reference 30

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source=pdf_text observed=2026-08-06T23:42:13.835352Z digest=sha256:b5f6157aa75735fe7c0b1db656fde54790e78a2eaf038cdcde4708e6e80d9257

Observation 415cc374-63b0-41e5-b226-faf467bbe0d1 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.

LegiGPT: Party Politics and Transport Policy with Large Language Model Lightgbm: A highly efficient gradient boosting decision tree

Reference 31

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source=pdf_text observed=2026-08-06T23:42:13.847824Z digest=sha256:d8f1c7266f28fdae7a364e70cb8ad6714fb269460ba058db08fd8633e3f337fc

Observation c7928aa5-9d89-415d-8d6d-65ca87d96536 · outbound

This paper cites Xgboost: A scalable tree boosting system.

LegiGPT: Party Politics and Transport Policy with Large Language Model Xgboost: A scalable tree boosting system

Reference 32

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Observation caeb4cf3-100a-4c6c-9663-030b41613272 · outbound

This paper cites On the possibility of short-term traffic prediction during disaster with machine learning approaches: An exploratory analysis.

LegiGPT: Party Politics and Transport Policy with Large Language Model On the possibility of short-term traffic prediction during disaster with machine learning approaches: An exploratory analysis

Reference 33

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 236abfdb-24b5-4296-9660-bd6844cd2934 · outbound

This paper cites Container terminal daily gate in and gate out forecasting using machine learning methods.

LegiGPT: Party Politics and Transport Policy with Large Language Model Container terminal daily gate in and gate out forecasting using machine learning methods

Reference 34

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.905343Z digest=sha256:cf2338ab0843928aa16071904749578c9fe9c4d08b1d2c9dcdf71a6c2572dee5

Observation 9bb0b1b2-f8f6-405c-8b0b-fd1851029d58 · outbound

This paper cites explainable dea approach for evaluating performance of public transport origin- destination pairs.

LegiGPT: Party Politics and Transport Policy with Large Language Model explainable dea approach for evaluating performance of public transport origin- destination pairs

Reference 35

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raw_fallback, observed 2026-08-06T23:42:14.205325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.918016Z digest=sha256:08c557e962c4d70cf78d0b0f7b0f7f5002a6360b56d63d4f75e97aec1d26b779

Observation 29172e70-2a4f-4f52-8e18-a99a668d9541 · outbound

This paper cites Impact of road transport system on groundwater qual- ity inferred from explainable artificial intelligence (xai).

LegiGPT: Party Politics and Transport Policy with Large Language Model Impact of road transport system on groundwater qual- ity inferred from explainable artificial intelligence (xai)

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.194301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.921574Z digest=sha256:2b29f28549eb31e91bdb6d354598dde4e8a976001cdd95ab0138326d3ded467a

Observation a71b7796-3027-4c0e-a3f2-3de680be3a8b · outbound

This paper cites an unresolved cited work.

LegiGPT: Party Politics and Transport Policy with Large Language Model Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:42:14.176099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.925717Z digest=sha256:a197a38a71ad72c5e61f0cbc323b9ada6990ccbe0acd406f00b693f0dcc8bb69

Observation e5c0e0d0-844a-47ee-a187-82733e25fdb9 · outbound

This paper cites Estimating express train preference of urban railway passengers based on extreme gradient boosting (xgboost) using smart card data.

LegiGPT: Party Politics and Transport Policy with Large Language Model Estimating express train preference of urban railway passengers based on extreme gradient boosting (xgboost) using smart card data

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.161903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.937265Z digest=sha256:53324922940b76950708641c57f3f2ed4140bba0f7fec275041b95450ab7318c

Observation ecc33b0e-9923-48a3-bd24-33027eb95a5a · outbound

This paper cites Experimenting xgboost algorithm for prediction and classification of different datasets.

LegiGPT: Party Politics and Transport Policy with Large Language Model Experimenting xgboost algorithm for prediction and classification of different datasets

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.147847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.946814Z digest=sha256:c875f10f5f762fbd8f8ad1a9e64c8124beac85ebf9d42a6274593ef1235fe4c5

Observation aa5d42b3-4a5d-456d-b00c-8de72f05a706 · outbound

This paper cites Would americans pay more in taxes for better transportation? answers from seven years of national survey data.

LegiGPT: Party Politics and Transport Policy with Large Language Model Would americans pay more in taxes for better transportation? answers from seven years of national survey data

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.136385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.954752Z digest=sha256:2df5632eb3d432e2e3b5ad43598d1e246292c09a9997ed3c7859fb57c2a78cc9

Observation 02008add-a6e0-4d42-8a0a-a3ce9cafb956 · outbound

This paper cites Policy feedback in an age of polarization, 2019.

LegiGPT: Party Politics and Transport Policy with Large Language Model Policy feedback in an age of polarization, 2019

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.125367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.966778Z digest=sha256:5992b21e3912c3ef059d201ed72c21cd23be9c145593833c248477b7bae4c0cb

Observation 813d3da6-e699-4544-89c5-75bbcfe750e2 · outbound

This paper cites The politics of sustainable development opposition: State legislative efforts to stop the united nation’s agenda 21 in the united states.

LegiGPT: Party Politics and Transport Policy with Large Language Model The politics of sustainable development opposition: State legislative efforts to stop the united nation’s agenda 21 in the united states

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.105767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.970588Z digest=sha256:f4abe8e99c5789ceceed8a29aa49bea0ea628975ddf4acad45d53048d19f570e

Observation 8c90bf49-7213-493a-aa83-e1b7ffc2bb2d · outbound

This paper cites Towards sustainable neighbourhoods? tensions and heterogeneous transport priorities among suburban residents.

LegiGPT: Party Politics and Transport Policy with Large Language Model Towards sustainable neighbourhoods? tensions and heterogeneous transport priorities among suburban residents

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:42:14.093423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T23:42:13.975230Z digest=sha256:fa6e31f32bcd80a52a6afb4334159c0e6c9aa1dc582861dcc16616966520a14d

Pith citing papers

No inbound Pith citation observations are available.