WEBVTT 00:00:00.000 --> 00:00:03.060 Welcome to today's deep dive. You are tuning 00:00:03.060 --> 00:00:06.059 in because you want to get past the surface level 00:00:06.059 --> 00:00:08.720 headlines, right? You want to understand the 00:00:08.720 --> 00:00:11.939 hidden architecture behind the information we 00:00:11.939 --> 00:00:15.480 consume every single day. Exactly. And today's 00:00:15.480 --> 00:00:19.100 source material is, well, on its face. It appears 00:00:19.100 --> 00:00:21.780 to be the most rigid, structured type of information 00:00:21.780 --> 00:00:23.940 possible. Yeah, we are looking at a Wikipedia 00:00:23.940 --> 00:00:26.620 article that is literally just titled List of 00:00:26.620 --> 00:00:28.960 United States senators from Colorado. Which, 00:00:29.039 --> 00:00:30.679 you know, sounds pretty dry. It's essentially 00:00:30.679 --> 00:00:33.119 just a giant data table. Right. It's just columns, 00:00:33.179 --> 00:00:35.700 columns for names, dates in office, political 00:00:35.700 --> 00:00:37.899 parties, hometowns. And most people would scan 00:00:37.899 --> 00:00:40.039 something like this just to settle a trivia bet, 00:00:40.159 --> 00:00:41.679 you know, and then immediately close the tab. 00:00:41.759 --> 00:00:44.299 Oh, absolutely. But our mission today is to show 00:00:44.299 --> 00:00:46.399 you that a chronological list of elected officials 00:00:46.399 --> 00:00:48.899 is actually it's a map. It's a map of political 00:00:48.899 --> 00:00:51.039 volatility. Yeah. When we start actually looking 00:00:51.039 --> 00:00:53.140 at the gaps, the overlapping dates and the sudden 00:00:53.140 --> 00:00:55.609 shifts in these columns, we are looking at. a 00:00:55.609 --> 00:00:58.869 150 -year timeline of human unpredictability. 00:00:59.090 --> 00:01:01.670 We are going to extract the actual narrative 00:01:01.670 --> 00:01:03.630 from that spreadsheet. So we're going to look 00:01:03.630 --> 00:01:06.430 closely at this data set to uncover the administrative 00:01:06.430 --> 00:01:10.530 chaos of early statehood, the structural implications 00:01:10.530 --> 00:01:13.290 of where these politicians actually live. Which 00:01:13.290 --> 00:01:15.349 is huge, by the way. Right, and the incredible 00:01:15.349 --> 00:01:17.750 ripple effects that happen when a single seat 00:01:17.750 --> 00:01:20.849 in Washington suddenly becomes vacant. So let's 00:01:20.849 --> 00:01:22.750 start right at the beginning of the timeline. 00:01:23.819 --> 00:01:27.560 the 1870s yeah let's do it the data shows colorado 00:01:27.560 --> 00:01:30.980 officially became a state on august 1st 1876 00:01:30.980 --> 00:01:33.900 but the dates in office for their very first 00:01:33.900 --> 00:01:36.879 senators don't actually align with statehood 00:01:37.290 --> 00:01:39.269 Right. The state didn't actually elect its senators 00:01:39.269 --> 00:01:42.750 until November 15th, 1876. That three -month 00:01:42.750 --> 00:01:45.349 gap is so interesting. It really is. It's a great 00:01:45.349 --> 00:01:47.549 indicator of the logistical scramble of early 00:01:47.549 --> 00:01:49.769 statehood. I mean, transitioning from a territory 00:01:49.769 --> 00:01:52.230 to a state means building electoral infrastructure 00:01:52.230 --> 00:01:54.750 essentially from scratch. And once they finally 00:01:54.750 --> 00:01:56.890 held those elections in November, they couldn't 00:01:56.890 --> 00:01:58.650 just send two people to Washington on their own 00:01:58.650 --> 00:02:01.650 schedule. No, because Colorado was entering an 00:02:01.650 --> 00:02:04.500 already established Senate. So they had to immediately 00:02:04.500 --> 00:02:07.799 slot their new senators into the chamber's existing 00:02:07.799 --> 00:02:11.060 staggered election cycles. The timeline shows 00:02:11.060 --> 00:02:13.479 Colorado's first senators were assigned to Class 00:02:13.479 --> 00:02:16.219 2 and Class 3. Which means from day one, those 00:02:16.219 --> 00:02:18.379 two seats were on completely different electoral 00:02:18.379 --> 00:02:20.960 clocks just to keep the national cycle balanced. 00:02:21.240 --> 00:02:23.300 Looking at the entries for that first delegation 00:02:23.300 --> 00:02:26.159 sent to Washington on November 15th, we have 00:02:26.159 --> 00:02:28.879 Jerome B. Chaffee. Elected to Class 3. Right, 00:02:28.919 --> 00:02:31.280 elected to Class 3. And he listed his hometown 00:02:31.280 --> 00:02:34.469 as Denver. And then Henry M. Teller elected to 00:02:34.469 --> 00:02:37.409 class two out of Central City. And tracking Henry 00:02:37.409 --> 00:02:40.009 M. Teller's timeline through this data reveals 00:02:40.009 --> 00:02:42.569 a massive footprint on the state's early political 00:02:42.569 --> 00:02:45.009 history. He really set the standard. He holds 00:02:45.009 --> 00:02:47.229 the record as Colorado's longest serving senator. 00:02:47.430 --> 00:02:51.069 He served his initial run from 1876 to 1882. 00:02:51.349 --> 00:02:53.229 And then the dates show him returning to the 00:02:53.229 --> 00:02:55.909 Senate a few years later. Yeah, 1885. And he 00:02:55.909 --> 00:02:58.729 maintains that seat all the way until 1909. That 00:02:58.729 --> 00:03:01.129 is over three decades of shaping the federal 00:03:01.129 --> 00:03:04.069 representation of a newly minted state. The party 00:03:04.069 --> 00:03:06.189 affiliation column for Teller is where the data 00:03:06.189 --> 00:03:09.550 captures a really highly specific snapshot of 00:03:09.550 --> 00:03:12.949 late 19th century American politics. It's a fascinating 00:03:12.949 --> 00:03:15.259 detail. We're so used to seeing this monolithic 00:03:15.259 --> 00:03:18.219 wall of Democrat or Republican in these tables. 00:03:18.560 --> 00:03:21.020 Teller started out as a Republican, but later 00:03:21.020 --> 00:03:24.219 in his tenure, around 1897, his party label shifts 00:03:24.219 --> 00:03:27.740 to silver Republican. It is incredibly rare to 00:03:27.740 --> 00:03:31.699 see a party designation tied to a single hyperspecific 00:03:31.699 --> 00:03:34.750 economic issue in a modern data set. It really 00:03:34.750 --> 00:03:37.310 breaks the rigid binary we expect in political 00:03:37.310 --> 00:03:39.310 data, doesn't it? It shows us that during the 00:03:39.310 --> 00:03:42.030 late 1890s, the national debate over currency, 00:03:42.210 --> 00:03:45.050 specifically the push to back currency with silver, 00:03:45.210 --> 00:03:48.050 was such an existential economic issue for a 00:03:48.050 --> 00:03:50.129 mining state like Colorado that it literally 00:03:50.129 --> 00:03:52.949 fractured national party lines. A senator's alignment 00:03:52.949 --> 00:03:55.650 with the local silver economy superseded traditional 00:03:55.650 --> 00:03:58.169 party loyalty. Completely, to the point where 00:03:58.169 --> 00:04:00.430 it required a completely separate official classification. 00:04:00.889 --> 00:04:03.629 That dynamic of sudden disruptive change is a 00:04:03.719 --> 00:04:05.360 recurring theme as you move down the columns 00:04:05.360 --> 00:04:07.300 here. Oh, definitely. If we look at the reasons 00:04:07.300 --> 00:04:10.319 why these terms ended, we see a striking parallel 00:04:10.319 --> 00:04:13.699 separated by over a century. Two different Colorado 00:04:13.699 --> 00:04:16.579 senators resigned their seats midterm for the 00:04:16.579 --> 00:04:19.000 exact same reason. To become the United States 00:04:19.000 --> 00:04:22.079 Secretary of the Interior. Yes. The first instance 00:04:22.079 --> 00:04:24.579 involves Henry M. Teller during his initial stint 00:04:24.579 --> 00:04:27.120 in the Senate. The record shows he resigned on 00:04:27.120 --> 00:04:30.699 April 17, 1882, to take on that cabinet role. 00:04:31.069 --> 00:04:33.110 Fast forward through the timeline to the modern 00:04:33.110 --> 00:04:36.009 era and the data mirrors itself perfectly. On 00:04:36.009 --> 00:04:40.069 January 20th, 2009, Class 3 Democrat Ken Salazar 00:04:40.069 --> 00:04:42.810 resigned from his Senate seat to take the exact 00:04:42.810 --> 00:04:45.529 same position of U .S. Secretary of the Interior. 00:04:45.980 --> 00:04:47.620 It functions almost like an intermittent pipeline 00:04:47.620 --> 00:04:49.720 from the Colorado Senate delegation directly 00:04:49.720 --> 00:04:51.819 to the Department of the Interior. And given 00:04:51.819 --> 00:04:54.480 the sheer volume of federal land within the state's 00:04:54.480 --> 00:04:57.040 borders, it makes structural sense that Colorado 00:04:57.040 --> 00:04:59.699 senators would develop the kind of land management 00:04:59.699 --> 00:05:01.939 background required for that specific cabinet 00:05:01.939 --> 00:05:04.740 position. It really does. But the data from 1882 00:05:04.740 --> 00:05:07.079 shows that Teller's resignation triggered an 00:05:07.079 --> 00:05:10.319 absolute administrative cascade. Midterm resignations 00:05:10.319 --> 00:05:12.519 forced the machinery of government to react immediately 00:05:12.519 --> 00:05:15.730 just to maintain continuous representation. Teller 00:05:15.730 --> 00:05:19.410 vacates the seat in April 1882. The vacancy must 00:05:19.410 --> 00:05:22.310 be filled, so George M. Chilcott is appointed 00:05:22.310 --> 00:05:25.110 to continue the term. But Chilcott's dates end 00:05:25.110 --> 00:05:27.730 before the term is actually up. Exactly. That 00:05:27.730 --> 00:05:29.709 leads to a special election to fill the remainder 00:05:29.709 --> 00:05:31.850 of the original timeline. Which results in one 00:05:31.850 --> 00:05:34.670 of the strangest entries in the entire data set. 00:05:35.110 --> 00:05:37.350 Horace Tabor is elected to finish out what's 00:05:37.350 --> 00:05:39.750 left of Teller's term. And look at Tabor's recorded 00:05:39.750 --> 00:05:44.160 dates in office. January 27, 1883 to March 3, 00:05:44.379 --> 00:05:47.779 1883. He held the office of United States Senator 00:05:47.779 --> 00:05:51.100 for just over a single month. A 35 -day tenure 00:05:51.100 --> 00:05:53.680 highlights the constitutional mandate for continuous 00:05:53.680 --> 00:05:56.079 representation colliding with practical reality. 00:05:56.339 --> 00:05:58.360 Right. From a legislative standpoint, a senator 00:05:58.360 --> 00:06:00.339 arriving in Washington for a month can accomplish 00:06:00.339 --> 00:06:02.879 almost nothing. They are sworn in, they might 00:06:02.879 --> 00:06:05.379 cast a handful of votes, and their term expires. 00:06:06.029 --> 00:06:08.449 But structurally, the seat cannot remain empty. 00:06:08.610 --> 00:06:10.709 The state goes through the entire process of 00:06:10.709 --> 00:06:12.769 an election just to ensure the seat is legally 00:06:12.769 --> 00:06:15.709 occupied until the next full cycle begins. Unfortunately, 00:06:15.949 --> 00:06:17.930 resignations are not the only cause of that kind 00:06:17.930 --> 00:06:20.790 of volatility. No, they aren't. Moving down the 00:06:20.790 --> 00:06:22.990 timeline into the early to mid -20th century, 00:06:23.209 --> 00:06:26.029 the reasons for terms ending shift pretty dramatically. 00:06:26.389 --> 00:06:29.050 There is a dense cluster of midterm deaths recorded 00:06:29.050 --> 00:06:32.050 here that completely upended the state's representation. 00:06:32.699 --> 00:06:34.899 It's a really grim pattern. Charles J. Hughes 00:06:34.899 --> 00:06:38.199 Jr. died in office in 1911, Samuel D. Nicholson 00:06:38.199 --> 00:06:42.860 in 1923, Charles W. Waterman in 1932, Alva B. 00:06:42.899 --> 00:06:46.420 Adams in 1941. That is four sitting U .S. senators 00:06:46.420 --> 00:06:49.519 dying midterm within a 30 -year span. The administrative 00:06:49.519 --> 00:06:51.459 gridlock that followed some of these tragedies 00:06:51.459 --> 00:06:53.620 was profound. Look at the timeline following 00:06:53.620 --> 00:06:56.279 the death of Charles J. Hughes Jr. The text records 00:06:56.279 --> 00:06:59.680 his death on January 11th, 1911. And the subsequent 00:06:59.680 --> 00:07:02.519 entry shows that the seat remained entirely vacant 00:07:02.519 --> 00:07:05.079 until Charles S. Thomas was elected to finish 00:07:05.079 --> 00:07:08.160 the term on January 15th, 1913. For two full 00:07:08.160 --> 00:07:10.439 years, the state of Colorado operated with only 00:07:10.439 --> 00:07:12.319 half its voice in the upper chamber. Which is 00:07:12.319 --> 00:07:15.120 wild. We just discussed the extreme lengths the 00:07:15.120 --> 00:07:17.439 state went to in the 1880s to fill a seat for 00:07:17.439 --> 00:07:20.000 35 days. Yet here, during the progressive era, 00:07:20.139 --> 00:07:23.279 a seat sits empty for 24 months. That implies 00:07:23.279 --> 00:07:25.920 a massive breakdown. in this state's ability 00:07:25.920 --> 00:07:28.139 to navigate the replacement process at the time. 00:07:28.240 --> 00:07:30.379 It creates a massive structural disadvantage 00:07:30.379 --> 00:07:33.579 for a state. It really does. And it also highlights 00:07:33.579 --> 00:07:35.660 the immense power of gubernatorial appointments 00:07:35.660 --> 00:07:38.379 when a replacement process does actually function. 00:07:39.120 --> 00:07:41.470 Look at the entry for Eugene Milliken. Right. 00:07:41.569 --> 00:07:44.189 Following the death of Alva B. Adams in December 00:07:44.189 --> 00:07:47.189 1941, Milliken was appointed to continue the 00:07:47.189 --> 00:07:49.170 term. He stepped in as an interim replacement, 00:07:49.430 --> 00:07:51.709 but the timeline shows he gets elected to finish 00:07:51.709 --> 00:07:55.189 the term in 1942, wins reelection, and stays 00:07:55.189 --> 00:07:58.370 in the Senate until 1957. A temporary appointment 00:07:58.370 --> 00:08:00.689 born out of a sudden death translated into a 00:08:00.689 --> 00:08:03.310 16 -year career. We can view that as the power 00:08:03.310 --> 00:08:05.670 of the unelected incumbent. An appointment grants 00:08:05.670 --> 00:08:08.339 the office, the staff, and the platform. By the 00:08:08.339 --> 00:08:10.019 time the special election actually occurs, the 00:08:10.019 --> 00:08:12.120 appointee already has the structural advantages 00:08:12.120 --> 00:08:14.540 of a sitting senator. Drastically changing the 00:08:14.540 --> 00:08:16.180 trajectory of the state's political history. 00:08:16.339 --> 00:08:19.079 That concept of sudden shifts, altering the balance 00:08:19.079 --> 00:08:21.899 of power, extends beyond vacancies, too. How 00:08:21.899 --> 00:08:25.040 so? Well, the data from the 1990s captures a 00:08:25.040 --> 00:08:27.670 different kind of instability. Ben Nighthorse 00:08:27.670 --> 00:08:29.629 Campbell was elected to the class three seat 00:08:29.629 --> 00:08:32.929 in 1992, listed as a Democrat from Ignacio. Oh, 00:08:32.970 --> 00:08:35.850 yes. The dates and office column notes a specific 00:08:35.850 --> 00:08:39.690 pivot. On March 3rd, 1995, right in the middle 00:08:39.690 --> 00:08:42.090 of his term, he changed his party affiliation 00:08:42.090 --> 00:08:44.409 to Republican. Party switching at the Senate 00:08:44.409 --> 00:08:47.330 level is structurally fascinating because it 00:08:47.330 --> 00:08:49.730 instantly alters the mathematics of the entire 00:08:49.730 --> 00:08:52.250 chamber without a single voter casting a ballot. 00:08:52.570 --> 00:08:54.610 Analyzing this purely from an impartial data 00:08:54.610 --> 00:08:57.190 perspective, a midterm shift of this magnitude 00:08:57.190 --> 00:09:00.129 is a massive event. It generally points to either 00:09:00.129 --> 00:09:02.610 rapidly changing political winds within the senator's 00:09:02.610 --> 00:09:06.009 home state or a significant ideological pivot 00:09:06.009 --> 00:09:08.610 by the representative themselves. It is a moment 00:09:08.610 --> 00:09:10.809 where the rigid columns of our spreadsheet capture 00:09:10.809 --> 00:09:13.730 a real -time, highly consequential human decision. 00:09:13.970 --> 00:09:16.210 Speaking of those rigid columns, the geographic 00:09:16.210 --> 00:09:18.730 data provided in this list reveals a massive 00:09:18.730 --> 00:09:21.809 structural trend. The hometowns. Yes, if you 00:09:21.809 --> 00:09:24.490 scan the hometown column for these senators over 00:09:24.490 --> 00:09:27.649 the course of 150 years, the repetition is impossible 00:09:27.649 --> 00:09:31.470 to ignore. Listen to this sequence. Chaffee from 00:09:31.470 --> 00:09:34.809 Denver, Hill from Denver, Wolcott, Patterson, 00:09:35.009 --> 00:09:37.769 Guggenheim. It just keeps going. It really does. 00:09:38.250 --> 00:09:42.110 Hughes, Thomas, Shafroth, Phipps, Nicholson, 00:09:42.309 --> 00:09:45.750 Waterman, Costigan, Schuyler, Milliken, Carroll, 00:09:45.929 --> 00:09:49.360 Salazar, Bennett, Hickenlooper. Generation after 00:09:49.360 --> 00:09:52.100 generation, the hometown listed is Denver. That 00:09:52.100 --> 00:09:54.100 repetition isn't just about where people happen 00:09:54.100 --> 00:09:55.960 to live. It is a map of the state's political 00:09:55.960 --> 00:09:58.480 infrastructure. Colorado is a geographically 00:09:58.480 --> 00:10:01.179 massive state with really diverse local economies. 00:10:01.399 --> 00:10:04.100 But historically, this data shows us that proximity 00:10:04.100 --> 00:10:06.320 to the capital city has been a prerequisite for 00:10:06.320 --> 00:10:09.080 federal representation. Denver holds the population 00:10:09.080 --> 00:10:11.120 density, the donor base, and the media markets 00:10:11.120 --> 00:10:13.379 necessary to build statewide name recognition. 00:10:14.009 --> 00:10:16.429 Which frames the rural senators on this list 00:10:16.429 --> 00:10:18.990 not just as geographic footnotes, but as significant 00:10:18.990 --> 00:10:21.730 structural anomalies. Exactly. You have Edwin 00:10:21.730 --> 00:10:24.070 C. Johnson from Craig in the Northwest, Gordon 00:10:24.070 --> 00:10:26.669 Allot from Lamar on the Eastern Plains, Horace 00:10:26.669 --> 00:10:28.669 Tabor during his brief tenure was from the high 00:10:28.669 --> 00:10:31.049 mountain town of Leadville. Right. And then Cory 00:10:31.049 --> 00:10:33.990 Gardner from Yuma and Walter Walker from Grand 00:10:33.990 --> 00:10:36.509 Junction on the Western Slope. For a candidate 00:10:36.509 --> 00:10:39.429 from a rural area to break through the political 00:10:39.429 --> 00:10:42.090 gravity of the capital city. They have to overcome 00:10:42.090 --> 00:10:45.129 immense logistical hurdles. The dominance of 00:10:45.129 --> 00:10:47.169 Denver in this data set proves that the urban 00:10:47.169 --> 00:10:49.669 center consistently churns out national level 00:10:49.669 --> 00:10:51.750 candidates. While a candidate from the eastern 00:10:51.750 --> 00:10:54.549 plains or the western slope has to build an entirely 00:10:54.549 --> 00:10:57.370 different kind of coalition to compensate for 00:10:57.370 --> 00:10:59.750 the lack of built in urban infrastructure. Moving 00:10:59.750 --> 00:11:02.190 down the timeline to the modern era, the data 00:11:02.190 --> 00:11:04.580 brings us to the current delegation. The state 00:11:04.580 --> 00:11:07.139 is currently represented by two Democrats. Michael 00:11:07.139 --> 00:11:09.980 Bennett in the Class 3 seat, serving since 2009 00:11:09.980 --> 00:11:12.679 after being appointed to fill Ken Salazar's vacancy, 00:11:12.779 --> 00:11:15.980 and John Hickenlooper in the Class 2 seat, serving 00:11:15.980 --> 00:11:19.179 since 2021. The text notes a specific statistical 00:11:19.179 --> 00:11:21.740 anomaly regarding this current delegation. Yes. 00:11:21.840 --> 00:11:24.139 In the Senate, seniority is determined by length 00:11:24.139 --> 00:11:26.440 of service. The person who has served longer 00:11:26.440 --> 00:11:28.740 is the senior senator, and the newer arrival 00:11:28.740 --> 00:11:31.529 is the junior senator. And in most cases, the 00:11:31.529 --> 00:11:33.830 senior senator is also chronologically older. 00:11:33.990 --> 00:11:37.389 But the data flags Colorado as one of 16 states 00:11:37.389 --> 00:11:40.610 where the senior senator, Michael Bennett, is 00:11:40.610 --> 00:11:42.769 actually younger in age than the junior senator, 00:11:43.009 --> 00:11:45.809 John Hickenlooper. A really fun trivia nugget. 00:11:45.889 --> 00:11:49.110 The article even provides the full list of the 00:11:49.110 --> 00:11:52.330 other 15 states sharing this age quirk. California, 00:11:52.710 --> 00:11:56.500 Delaware, Georgia, Hawaii. Idaho, Louisiana, 00:11:56.899 --> 00:11:59.980 Maine, Massachusetts, Minnesota, Missouri, Nevada, 00:12:00.240 --> 00:12:02.919 Pennsylvania, South Dakota, Utah, and West Virginia. 00:12:03.320 --> 00:12:06.039 But if we look at the metadata right at the end 00:12:06.039 --> 00:12:08.639 of that list, there's a bracketed tag embedded 00:12:08.639 --> 00:12:11.440 in the text. Right. It reads, not verified in 00:12:11.440 --> 00:12:13.960 body. The classic Wikipedia warning label. It's 00:12:13.960 --> 00:12:15.879 sitting right there attached to the trivia. It 00:12:15.879 --> 00:12:18.419 is a vital reminder of the mechanics of crowdsourced 00:12:18.419 --> 00:12:20.919 information. A data table presents itself as 00:12:20.919 --> 00:12:23.610 absolute authority. But a tag like that means 00:12:23.610 --> 00:12:25.649 an editor inserted this comparative statistic 00:12:25.649 --> 00:12:28.669 into the introduction without providing the corresponding 00:12:28.669 --> 00:12:31.009 citations in the main text to back up the math 00:12:31.009 --> 00:12:33.570 for all 16 states. It doesn't inherently mean 00:12:33.570 --> 00:12:36.250 the trivia is false, but it serves as a built 00:12:36.250 --> 00:12:38.330 -in admission of the source's own limitations. 00:12:38.909 --> 00:12:42.009 Exactly. It forces the reader to practice source 00:12:42.009 --> 00:12:44.769 literacy and maintain a level of skepticism, 00:12:44.889 --> 00:12:47.789 even with seemingly harmless statistical quirks. 00:12:47.889 --> 00:12:50.230 We started this deep dive looking at what appeared 00:12:50.230 --> 00:12:53.830 to be a static dry timeline of names and dates. 00:12:54.090 --> 00:12:56.769 But by analyzing the anomalies, the gaps, and 00:12:56.769 --> 00:12:59.090 the repetitions, a much more complex picture 00:12:59.090 --> 00:13:01.190 emerges. We've tracked the logistical hurdles 00:13:01.190 --> 00:13:03.289 of aligning a new state with federal election 00:13:03.289 --> 00:13:06.529 cycles, the constitutional friction of a 35 -day 00:13:06.529 --> 00:13:09.149 term, and the sheer administrative breakdown 00:13:09.149 --> 00:13:12.289 of a two -year vacancy. We also mapped the pipeline 00:13:12.289 --> 00:13:14.529 from the Senate to the Department of the Interior, 00:13:14.769 --> 00:13:17.549 the overnight structural shifts caused by midterm 00:13:17.549 --> 00:13:19.730 party changes, and the overwhelming political 00:13:19.730 --> 00:13:22.750 gravity of a single capital city over a century 00:13:22.750 --> 00:13:25.450 and a half. Information is just data until you 00:13:25.450 --> 00:13:28.049 look at the human timeline behind it. The data 00:13:28.049 --> 00:13:30.490 is only static until you recognize that every 00:13:30.490 --> 00:13:32.929 start date, end date and hometown represents 00:13:32.929 --> 00:13:35.710 a shifting political ecosystem. Connecting the 00:13:35.710 --> 00:13:37.789 dots is really what it's all about. Before we 00:13:37.789 --> 00:13:39.830 wrap up, I want to leave you with a final thought 00:13:39.830 --> 00:13:42.750 to consider on your own. We spent a significant 00:13:42.750 --> 00:13:45.370 amount of time unpacking the absolute dominance 00:13:45.370 --> 00:13:48.830 of Denver in that hometown column. A huge concentration 00:13:48.830 --> 00:13:52.139 of power. Right. Given that immense urban concentration 00:13:52.139 --> 00:13:55.639 of political power, consider the tension it creates. 00:13:55.919 --> 00:13:58.559 How might the needs of the vast, diverse, and 00:13:58.559 --> 00:14:01.039 remote parts of Colorado, the farming communities, 00:14:01.299 --> 00:14:03.779 the mining towns, the agricultural hubs, have 00:14:03.779 --> 00:14:06.399 forced those urban -based politicians to adapt 00:14:06.399 --> 00:14:08.539 their legislative strategies? That's a great 00:14:08.539 --> 00:14:11.519 question. To maintain statewide power decade 00:14:11.519 --> 00:14:14.960 after decade, an urban politician must eventually 00:14:14.960 --> 00:14:18.539 answer to a rural frontier. It is a dynamic of 00:14:18.539 --> 00:14:21.279 compromise and strife that isn't explicitly written 00:14:21.279 --> 00:14:23.620 in the columns of a spreadsheet, but is absolutely 00:14:23.620 --> 00:14:26.279 essential to surviving in public office. It's 00:14:26.279 --> 00:14:28.940 the hidden story behind the data. Exactly. Keep 00:14:28.940 --> 00:14:31.399 questioning the data, keep looking for the hidden 00:14:31.399 --> 00:14:33.639 infrastructure behind the facts, and we will 00:14:33.639 --> 00:14:34.580 catch you next time.