“All this My pleasuare to be here, to introduce. Some of you may call him Bobby some of you call him Zimmy. I call him Lucky. Ladies and gentleman, please welcome Bob Dylan.”
Audio of Bob telling the audience he doesn't know anyone named "Bob" (happens at 1:16 mark) Port Chester Nov 23, 2021 Maybe we just call him Mr. Dylan. Or Robert. youtube.com/watch?v=53Sqx5…
Philippe Lemoineというコーネルの博士課程にいる研究者が、自らが所属するThe Center for the Study of Partisanship and Ideology（CSPI）という組織のブログに「Have we been thinking about the pandemic wrong? The effect of population structure on transmission」と題した長文のエントリを上げ、タイラー・コーエンが「Why does R vary so much in pandemics?」というコメントを添えて リンクしている。Lemoineはツイートでその内容を解説しているので、以下にその一部を引用してみる。
However, as I argue in the post, I think it's very difficult to deny that the effective reproduction number can undergo large fluctuations even in the absence of significant behavioral changes, which is hard to understand. Of course, there are other factors that influence transmission (such as meteorological variables), but I argue in the post that they are not sufficient to explain the large fluctuations of the effective reproduction number we observe in the absence of behavioral changes. Since SARS-CoV-2 is a respiratory virus that is transmitted by contact, transmission should ultimately depend on people's behavior, this is very puzzling. So how can we explain those fluctuations of the effective reproduction number without denying this basic fact? What I propose in the post is that we can square this circule by taking into account population structure and how it can affect transmission even in the absence of behavioral changes. Indeed, standard epidemiological models, of the sort that are used to make projections and study the impact of non-pharmaceutical interventions, assume that the population is homogeneous mixing or something close to it. What this means is that models assume that someone who is infectious has the same probability of infecting everybody in the population or, since models used in applied work often divide the population into age groups, the same probability of infecting everyone in their age group. Of course, this is totally unrealistic, since in practice if I'm infectious the probability that I'll infect most people in the population or even in my age group is effectively zero, because I don't even have any interaction with them and therefore couldn't possibly infect them. In practice, the virus doesn't spread in a homogeneous population, but on a network based on people's patterns of interaction with each other. The topology of that network determines what paths the virus can take to spread on the population and not all paths are equally likely. Now, suppose that this network can be divided into subnetworks that are internally well-connected, but only loosely connected to each other. In network science, a network that has this property is said to have "community structure", which many real networks are observed to have. For instance, here is a network based on friendship relationships among a few thousand people on Facebook, which has this kind of structure. If the population has that kind of structure, when one of the subnetworks is seeded, the virus starts spreading in that subnetworks until herd immunity is reached locally, at which point incidence goes down unless the virus manages to reach another subnetwork from there. Thus, instead of simulating the spread of the virus on a network of individuals, I simulate the spread on a network of homogeneous mixing populations that has community structure. Here is a graph that shows the network generated by the model for one of my simulations. At the level of each subpopulation in the network, the model is a standard epidemiological model that assume homogeneous mixing, but people who are infected in one subpopulation can "travel" to another along the edges of the network and infect people over there. (I put "travel" in scare quotes because people in different subpopulations may nevertheless be neighbors. What matters is who they interact with, not physical proximity, though obviously they are related. I discuss this point in more detail in the post.) As you can see, the network is divided into subnetworks that are internally well-connected, but loosely connected to each other. Moreover, each edge is associated with a probability of "travel" along that edge, which is much greater for edges that stay within the same subnetwork. For this simulation, I assumed a probability of "travel" of 5% along the edges that stay within the same subnetwork, but only 1 in 10,000 for edges that lead to a subpopulation in another subnetwork. There are more than 10,000 subpopulations, for a total population of ~5 million. Here is a chart that shows the result of the simulation when I let the virus spread on that network. As you can see, the effective reproduction number undergoes wild fluctuations and the population experiences several waves at the aggregate level. However, at the level of each subpopulation, the basic reproduction number was assumed to remain constant! Thus, this shows that, when the population has that kind of structure, the effective reproduction number can undergo large fluctuations even without any behavioral changes. In order to make the process more intuitive, I created this animation showing how the virus spreads across subpopulations, which are represented by rectangles whose area is proportional to their size inside larger rectangles that represent the subnetworks to which they belong. Unsurprisingly, if we increase the connectivity between subnetworks enough, the model behaves in a way that is more similar to what happens in a homogeneous mixing population. For instance, if I use the same method to randomly generate a network but multiply the average number of edges between subnetworks by 10 and the probability of "travel" associated to those edges by 100, I obtain this epidemic. Simulations on networks with community structure can produce all sort of epidemics, not just epidemics with large, sharply defined waves as above, but also epidemics that exhibit long plateaus with ups and downs. Just as we see in real data. Thus, by relaxing the assumption of homogeneous population mixing and simulating the spread of the virus on a network with community structure, we can get the sort of behavior that we observe in the real world even with a constant basic reproduction number in each subpopulation. （拙訳） しかしながら、エントリで論じたように、行動の顕著な変化が無くても実効再生産数が大きく振れることがあるのを否定するのは非常に難しいと思う。この現象を理解するのは困難である。 もちろん、感染に影響する要因は（気象変数など）他にもあるが、エントリで論じたのは、行動の変化が無い場合に我々が観測する実効再生産数の大きな振れを説明するのにそれらは十分ではない、ということである。 SARS-CoV-2は接触感染する呼吸器系のウイルスであり、感染は結局は人々の行動に依存するはずなので、この現象は非常に不思議である。基本的な事実を否定することなしに実効再生産数のこの振れをどのように説明できるだろうか？ エントリで私が提案したのは、人口構造と、行動の変化が無い場合でもそれがどのように感染に影響するか、を考慮に入れれば、この難題を解決できる、ということである。 実際のところ、予測や非医薬的措置の効果の研究に使われるような標準的な疫学モデルでは、人口は均一な混合物ないしそれに近いものと仮定されている。 そのことが意味するのは、感染した人が人口の誰かに感染させる確率は皆等しい、とモデルが仮定している、ということである。あるいは、応用研究では人口を年齢層に分けることが多いので、その年齢層で誰かに感染させる確率は皆等しい、とモデルが仮定している、ということである。 もちろんこれは完全に非現実的である。実際には、私が感染したら、人口の大半、もしくは同じ年齢層の人の大半でさえ、私が感染させる確率は事実上ゼロである。というのは、彼らとは一切関わりがなく、従って感染させ得ないからである。 実際にはウイルスは均一な人口に広がるのではなく、人々の相互の関わりのパターンに基づくネットワークの上で広がる。そのネットワークのトポロジーが、ウイルスが人口に広まる際に採り得る経路を決定し、すべての経路の確率は同じではない。 このネットワークが、内部での接続は強いが、お互いの接続は弱い副ネットワークに分割することができるとしよう。 ネットワーク科学では、このような特性を持つネットワークは「共同体構造」を持つ、と言われ、実際のネットワークの多くがその特性を持っていることが観測されている。例えば、以下はフェイスブックの数千の人々の友だち関係に基づくネットワークであるが、そうした構造を持っている。 人口がこのような構造を持っている場合、副ネットワークの一つに種が蒔かれれば、ウイルスはその副ネットワークに広がり始め、それは局所的な集団免疫が達成されるまで続く。ウイルスがそこから他の副ネットワークに到達しない限り、その時点で感染は収束する。 ということで私は、個々人のネットワーク上でウイルス拡散をシミュレートする代わりに、共同体構造を持つ均一混合人口のネットワーク上でシミュレートした。私のシミュレーションの一つでモデルが生成したネットワークを示すグラフは以下の通り。 ネットワークのそれぞれの副人口のレベルでは、モデルは、均一混合を仮定する標準的な疫学モデルである。しかしある副人口の感染者はネットワークの枝に沿って別の副人口に「旅行」することができ、そこの人々に感染させることができる。 （「旅行」を鍵括弧に入れたのは、異なる副人口の人々が実は近所だということがあり得るからである。重要なのは誰と関わるかであり、物理的な近さではない。とは言え、その２つが関連しているのは明白である。この点はエントリでより詳細に論じた。） 見て分かるように、ネットワークは、内部での接続は強いが、お互いの接続は弱い副ネットワークに分割されている。また、それぞれの枝はその枝に沿って「旅行する」確率と関連しているが、同じ副ネットワーク内の枝ではその確率はかなり高い。 このシミュレーションのため私は、同じ副ネットワーク内の枝に沿って「旅行」する確率を5%としたが、他の副ネットワークの副人口につながる枝については1万分の1とした。副人口は1万以上あり、総人口は約500万である。 このネットワークでウイルスを拡散させたシミュレーション結果のグラフは以下の通り。見て分かる通り、実効再生産数は大きく振れ、人口は全体レベルで幾つかの波を経験する。 しかしそれぞれの副人口レベルでは、基本再生産数は一定に留まると仮定しているのである！ ということで、このことが示しているのは、人口にこうした構造がある場合、行動が何も変化しなくても実効再生産数は大きく振れることがある、ということである。 この過程をより直観的に分かりやすくするため、ウイルスが副人口間でどのように拡散するかを示す以下のアニメーションを作成した。副人口は面積が人口規模に比例する長方形で表されており、所属する副ネットワークを表すより大きな長方形の中にある。 twitter.com
Based on the response to this post, many people seem to think what I'm saying is the same thing as what people who argued back in 2020 that heterogeneity in social activity might lower the herd immunity threshold, but while this is related to what I'm talking about here it's actually different so I thought it might be useful to briefly explain why. I'm actually familiar with the debate that took place about that last year, since I even wrote a post about it at the time. In both cases, the point is that heterogeneity affects the dynamic of the epidemic, but it's not the same kind of heterogeneity. What people were arguing last year is that, if people's level of social activity varies a lot, herd immunity will be reached sooner because the people who spread the virus the most are also the most likely to be infected early in the pandemic.41 This intuitive argument is supported by models showing that, when you introduce that kind of heterogeneity, herd immunity does in fact occur sooner. If we model the spread of the virus on a network, this debate was mostly about the degree distribution, i. e. the distribution of the number of edges connected to each individual in the network. The point was that, when this distribution is more dispersed than standard epidemiological models implicitly assume, the herd immunity threshold will be lower than predicted by those models. However, the kind of epidemic behavior I discuss in this post only arises when the network has community structure, which is about a lot more than the variance of the degree distribution.42 In particular, the network must exhibit a specific kind of clustering, but this doesn't just depend on its degree distribution. In fact, it's conceivable that at the level of the parts of the network that I idealized as homogeneous mixing population in my simulations, the herd immunity threshold is lower than predicted by standard epidemiological model due to heterogeneity in social activity, even though at the aggregate level it's higher due to community structure, as I explained above. So while most people have interpreted the fact that many places with a high prevalence of immunity have recently experienced large outbreaks as proof that people who argued that heterogeneity in social activity could lower the herd immunity threshold were wrong, this is not actually the case if the network on which the virus is spreading has the kind of structure assumed in this post. Of course, like the rest of this post, this is very speculative, but it goes to show that the spread of infectious diseases is a lot more complicated than people generally assume. （拙訳） このエントリへの反応を見ると、私の言っていることは、社会活動の不均一性が集団免疫の閾値を下げるかもしれないと2020年に人々が論じていたのと同じこと、と多くの人が考えているようである。しかし、その話はここで私の言っていることと関連はしているものの、実際には違う。その理由を簡単に説明するのは有益かと思われる。昨年のその議論については私もよく知っているが、というのは当時それについてエントリを書いてさえいるからだ。いずれのケースでも、不均一性が疫病の動学に影響することがポイントとなっているが、両者の不均一性は同じものではない。昨年人々が論じていたのは、人々の社会活動の水準のばらつきが大きければ、集団免疫は早く達成できる、ということである*1。そうした不均一性を導入すれば実際に集団免疫は早く達成される、ということを示したモデルにより、この直観的な議論は支持された。ウイルスのネットワーク上での拡散をモデル化する場合、この議論は主に次数分布、即ち、ネットワークで個人が互いに接続されている枝の数の分布に関する話となる。そこでのポイントは、この分布が標準的な疫学モデルが暗黙裡に仮定しているよりも分散しているならば、集団免疫の閾値はそれらのモデルが予測するよりも低くなる、ということである。 しかし、私が本エントリで論じている疫学的振る舞いは、ネットワークが共同体構造を持っている場合のみ生じる。それは次数分布の分散よりもかなり広い話である*2。具体的には、ネットワークはある種のクラスタリングを示す必要があるが、これは次数分布だけに依存するわけではない。実際、私がシミュレーションで均一混合人口として理想化したネットワークの部分レベルでは、集団免疫の閾値は社会活動の不均一性によって標準的な疫学モデルが予測するよりも低くなる。上で説明したように、共同体構造のために全体レベルでは閾値は高くなるにもかかわらず、である。免疫が普及した多くの場所で最近大規模なコロナ禍が生じたことを、社会活動の不均一性が集団免疫の閾値を下げると論じた人が間違っていたことを証明した、と多くの人は解釈したが、ウイルスが拡散しているネットワークが本エントリで仮定したような構造を持っていたとしたら、それは必ずしもそうではない。もちろん、エントリの他の部分と同様、これはまったく推測の域を出ない話であるが、感染症の拡大は人々が一般に想定するよりも遥かに複雑であることを示す話ではある。
*1:原注：Actually, some people also talked about other kinds of heterogeneity, such as heterogeneity in susceptibility. If you are modeling the spread of a virus on a network, whose edges have a weight indicating the probability of transmission along that edge, this presumably depends on a combination of the degree distribution and the distribution of the weights. But this is also different from the kind of heterogeneity I'm discussing in this post. （拙訳） 実際には、感受性における不均一性など、他の種類の不均一性について論じた人もいた。枝に沿った感染確率を示すウエイトを備えたネットワークでウイルス拡散をモデル化する場合、これは次数分布とウエイトの分布との組み合わせに左右されると思われる。しかしそれは本エントリで私が論じている不均一性とはやはり違う。
*2:原注：In general, the topology of a network can't be reduced to the properties of its degree distribution, because it depends on facts about how the network was generated that go beyond the degree distribution that was used. （拙訳） 一般にネットワークのトポロジーは次数分布の特性に還元できない。ネットワークがどのように生成されたかという、使われた次数分布を超えた話に依存するからである。
D Livin' on the road, my friend A Was gonna keep us free and clean G But now you wear your skin like iron D A And your breath's as hard as kerosene G You weren't your mama's only boy D G But her favorite one, it seems Bm She began to cry G A When you said good bye G Bm And sank into your dreams
Pancho was a bandit, boys Rode a horse fast as polished steel Wore his guns outside his pants For all the honest world to feel Pancho met his match, you know On the deserts down in Mexico No one heard his dyin' words But that's the way it goes
G And all the federales say D G They could have had him any day Bm G A They only let him slip away G Bm Out of kindness, I suppose
Now Lefty he can't sing the blues All night long like he used to The dust that Pancho bit down South It ended up in Lefty's mouth The day they laid old Pancho low Lefty split for Ohio Where he got the bread to go Well there ain't nobody 'knows
But all the federales say They could have had him any day They only let him slip away Out of kindness, I suppose
Now poets sing how Pancho fell Lefty's livin' in a cheap hotel The desert's quiet and Cleveland's cold And so the story ends, we're told Pancho needs your prayers, it's true But save a few for Lefty, too He only did what he had to do And now he's growin' old
And all the federales say They could have had him any day They only let him go so long (slip away) Out of kindness, I suppose
Yes a few old gray federales still say They could have had him any day They only let him go so wrong Out of kindness, I suppose
Watching The River Flow カントリー・ストンプ風の軽快なアレンジでオープニングにぴったりだ。ボブのヴォーカルがすばらしい。 途中でボブが単音で独特のピアノを弾く。
When You Go Your Way, I'll Go Mine 60年代を思い出させるような若々しく力強いヴォーカル。途中のブレイクではスローに変調し、ボブの説得力のあるヴォーカルを聴かせる。
I Contain Multitudes お待ちかねのニューアルバムから。イントロが始まるとすぐに観客が声援を上げる。みんなボブのファンだ。ボブがピアノを離れ、ステージセンターに立ってハンドマイクで歌い出す。ようやく表情が見えた。元気そうだ。ステージセンターと言っても、前に出てくるわけではない。奥に引っ込んだままだ。歌が始まると会場が静まり返る。一言も聞き漏らしたくないのだろう、ほとんどドラムレスのバックで、心に刺さるフレーズが歌われるたびに歓声が上がる。ボブは最初の数フレーズを歌うと、すぐにピアノに戻ってしまった。
When I Paint My Masterpiece ドニー・ヘロンがヴァイオリンを、ボブ・ブリットがアコースティックギターを弾き、これも軽快なカントリー・ナンバーに仕上がっている。ボブのピアノのリードに合わせて、ヴァイオリン、ギターでジャムセッションを繰り広げる。
Black Rider ボブは新曲を歌うときは、できるだけ頭の数フレーズをハンドマイクで歌おうと決めているようだ。この曲では不気味な雰囲気が醸し出され、語るように歌うボブのヴォーカルが会場を満たしていく。アメリカン・ソンングブック時代に高めた歌い方が活かされている。こんなヴォーカリストはほかにいない。最高だ。
I'll Be Your Baby Tonight オリジナルとはまるで違うアレンジ。リズムを効かせたチャック・ベリー風のロックンロールだ。間奏のボブのピアノ・ソロを聴きながら、ハイスクール時代のボブはこんな感じだったのかなと思ってしまった。
My Own Version Of You ストーリーテラーとしてのボブの本領が発揮される。不気味な物語が伝わって、ゾクゾクさせれる。それにしてもこれほど明瞭なヴォーカルを聴かせるボブは何年ぶりだろう。
Early Roman King ギターを強調したヘヴィーなブルースロックに生まれ変わった。チャーリー・セクストンがバンドを去ったことは悲しいが、ボブ・ブリットとダグ・ランシオのツインギターも悪くない。
To Be Along With You ピアノ、ヴァイオリン、アコースティックギターを効かせたホンキートンクナンバーにアレンジされている。ここでもボブの単音ピアノ・ソロが愉快に響く。
Key West ニューアルバムの中の最大注目曲の一つなので、イントロが始まると歓声が上がる。９分近い大作だが、ボブの歌によって観客は酔いしれるようにいつしかパラダイスに誘われ、夢見心地の世界が広まる。ドニー・ヘロンのアコーディオンが効果的に流れる。ボブはピアノから離れずに歌い続けた。
The composition became popular as the Wall Street Crash of 1929 in October led on to the Great Depression. The themes depicted on it became commonplace in the lives of unemployed Americans.[23] In respect to Rodgers' role, critic Dave Marshhas pointed out: "it was Rodgers—far more than Woody Guthrie—who was the true voice of the Depression".[24] In November 1929, Rodgers starred in the short The Singing Brakeman, by Columbia Pictures. Filmed on the Victor lot in Camden, New Jersey, the film depicted Rodgers singing in a railroad restaurant. It opened with "Waiting for a Train".[25]Rolling Stone later considered the film to be "one of the first-ever country music videos" and remarked upon Rodgers' understanding of the importance of trains as the subject of songs in the genre.[26]
"Waiting for a Train" is a song written and recorded by Jimmie Rodgers and released by the Victor Talking Machine Company as the flipside of "Blue Yodel No. 4" in February 1929. The song originated in the nineteenth century in England. It later appeared in several song books, with variations on the lyrics throughout the years.
Rodgers, who was familiar with the tune, reworked it with producer Ralph Peer. Complementary to Rodgers' characteristic blues guitar, the recording session featured a jazz combo the singer found while visiting a bar in Atlanta, Georgia, just before the recording session.
It became one of Rodgers' most popular songs, as the Wall Street Crash of 1929 made the composition relatable to everyday life during the Great Depression. Rodgers became the best selling act of the year. Since then, "Waiting for a Train" has been recorded by several other artists.
Contents
1Origins
2Recording
3Reception
3.1Legacy
4Chart performance
4.1Jerry Lee Lewis
5Footnotes
6References
Origins
The origins of the song were traced by D. K. Wilgus, a music scholar and professor at UCLA, to a mid-nineteenth-century broadside ballad printed by Catnach Press in London, entitled "Standing on the Platform", with the subtitle "Waiting for the train". The song recounted the story of a man who met a woman at a railway station, who later falsely accused him of assaulting her. Modified versions of the ballad appeared in diverse songbooks of the era, such as Billy Newcomb's San Francisco Minstrels' Songster (1868), Billy Cottons Ethiopian Songster (1870), a sheet music published by S. Brainard Sons (1870) and Coming Through the Rye (1871). In the 1880s, a version called "Wild and Reckless Hobo" was published.[1] In July 1909, the request of a reader for a complete version of a poem was published in the Railroad Man's Magazine. The man only knew the first two verses:[2]
While standing on the platform, waiting for the train, Cold and hungry, I lay down, out in the cold and rain Thinking o'er those good old times I ne'er shall see again, Ten thousand miles away from home, I've bummed a railroad-train.[3]
The request was not replied to, but the magazine printed the poem as "10,000 Miles From Home" five years later in 1914. Sociologists Guy Benton Johnson and Howard W. Odum collected verses of the song during their field research of black culture in the Southern United States in the late 1910s.[4] The composition was also traditionally known as "Danville Girl".[5] The earliest known recording of the song was made by George Reneau as "Reckless Hobo" on February 24, 1925, and released by Aeolian-Vocalion Records.[2] In 1929, Prince Albert Hunt released it as "Waltz of the Roses" on Okeh Records.[5]
Recording
Jimmie Rodgers started singing his own version of the song around early 1925. He later received a suggestion to record it in 1928.[6] Rodgers could only remember some of the words to the song. Since he was only able to play only a few chords on the guitar, he could not use the original tune.[7] He and producer Ralph Peer rewrote the lyrics to the song to fit Rodgers' guitar skills. The composition was at the time in the public domain, but with the changes in the lyrics and music, Peer decided he would be able to copyright it under Rodgers' name.[8][9] It was written in a six-line stanza.[10] "Waiting for a Train" told the story of a man, now turned a hobo, as he struggled to return to his home. He is found by a brakeman while riding through Texas, and thrown off of the boxcar to continue on foot.[11] The recording introduced Rodgers' trademark train whistle.[9] Rodgers produced the sound on the back of his throat by mixing a yodel with a whistle.[12]
Rodgers arrived in Atlanta, Georgia, a week before his recording session for the Victor Talking Machine Company was scheduled. While experiencing the night life of the city at a speakeasy, Rodgers encountered a jazz combo composed of Dean Bryan (guitar), C. L. Hutchinson (cornet), James Rikard (clarinet), George MacMillan (bass fiddle) and John Westbrook (steel guitar). Rodgers invited the group to join him in his upcoming session after trying out some songs with their backing.[13] In addition to Rodgers' characteristic blues guitar sound, the participation of the combo known as the Westbrook Conservatory Entertainers on "Waiting for a Train" gave the song a "jazz-flavored" sound.[14] After the train whistle, Rodgers sang the first verse and followed with his signature yodel. Then a dixieland-style breakdown composed of cornet and clarinet joined in,[15] with a long clarinet solo featured.[14] Rodgers followed with his guitar, accompanied by the steel guitar, both playing in the style of a twelve-bar blues.[16] The October 22 session took place between 9a.m. and 1p.m., and yielded the recordings of "Waiting for a Train" and "I'm Lonely and Blue".[5] The recording of "Waiting for a Train" was done in four takes, with the final one being selected as the master.[17]
It was paired with a song from a later session, "Blue Yodel No. 4", and was released on February 8, 1929, with the catalog number V-40014. It was copyrighted on March 23.[18] On the record pressing, "Waiting for a Train" was assigned to V-40014-B.[19] Victor added "A" and "B" at the end of the catalog number to differentiate the sides.[20] Before the 1930s, the songs contained in a record would be referred to as "sides", and promoted together equally. The names of the compositions were published with letters of the same size and font by record companies, accompanied by the catalog number of the releases. Reviewers of the time commonly mentioned both sides of the record without focusing on a particular song.[21]
The disk sold 365,000 copies upon its release, and became Rodgers' second-best-selling recording,[6] behind the pairing of "Blue Yodel No. 1 (T for Texas)" / "Away Out in the Mountain".[22] The Victor Talking Machine Company sound engineers later discovered that the strong sound of the bass fiddle on the original recording damaged the grooves as it was played. Victor re-dubbed the track, and later issues featured the bass sound cut in half.[14]
Reception
Advertising of the record, published in 1929 with Rodgers' Victor Records catalog
The composition became popular as the Wall Street Crash of 1929 in October led on to the Great Depression. The themes depicted on it became commonplace in the lives of unemployed Americans.[23] In respect to Rodgers' role, critic Dave Marsh has pointed out: "it was Rodgers—far more than Woody Guthrie—who was the true voice of the Depression".[24] In November 1929, Rodgers starred in the short The Singing Brakeman, by Columbia Pictures. Filmed on the Victor lot in Camden, New Jersey, the film depicted Rodgers singing in a railroad restaurant. It opened with "Waiting for a Train".[25]Rolling Stone later considered the film to be "one of the first-ever country music videos" and remarked upon Rodgers' understanding of the importance of trains as the subject of songs in the genre.[26]
Reviews of Rodgers' concerts that included the song at the time remarked it to be among the numbers which "proved most popular",[27] and remarked its appeal to the audiences.[28] Others referring to his blues guitar on the performances concluded that Rodgers "plays as entertainingly as he sings".[29]
Rodgers became the best-selling country act of 1929. Other labels started to look for artists that sounded like him to replicate his success.[30] Though it was at the time already considered a traditional song, Prince Albert Hunt claimed that Rodgers copied his record.[5] "Waiting for a Train" was first covered by Ed Jake West on the American Record Corporation label,[31] followed by Riley Puckett on Columbia Records.[32] In May 1929, Gene Autry released his own cover of the song,[30] with singer Frankie Marvin providing the whistle sound.[33] His producer, Art Satherley talked to him about not recording any more Rodgers covers. Since Autry had been covering many of Rodgers' songs soon after their release, Satherley felt he was becoming an imitator. The singles sold poorly, and he advised Autry to find better material.[30]
Legacy
Buddy Jones recorded it in 1940,[34] and Wilf Carter in 1941.[35]Ernest Tubb released it on Decca Records in 1948. Based on the aggregate score of 73 by operators, disk-jockeys and record dealers, Billboard deemed Tubb's version on its scale as "good".[36]
Robert Johnson's step-sister, Annye, remembered Rodgers as their favorite country singer. Johnson played "Waiting for a Train", and imitated Rodgers' yodel.[37]Johnny Cash included it in his album Blood, Sweat and Tears.[38] On May 10, 1962, Cash appeared at Carnegie Hall. A fan of Rodgers', Cash designed a concept show based around him. Rodgers' daughter lent him one of her fathers' costumes to wear during the appearance. Cash ordered the lights of the concert hall to be turned off, so he could be only illuminated during his entrance by a lantern that belonged to Rodgers. Following a Rodgers' signature move, Cash walked to a chair on the center of the stage, and put his knee on it. He opened with "Waiting for a Train".[39]George Harrison cited Rodgers as one of his early influences, and credited the pairing of "Blue Yodel No. 4" and "Waiting for a Train" owned by his father as the first guitar recordings he heard.[40]
Jim Reeves released it as the flip-side to his single "Am I Losing You" in 1956,[41] and then included it in his 1962 album The Country Side of Jim Reeves.[42]Furry Lewis re-recorded it as "Dying Hobo". It featured his own version of the yodel,[43] and it was released on the Blue Horizon label in 1969.[44]Merle Haggard recorded his own version for his 1969 tribute album Same Train, a Different Time.[45]Jerry Lee Lewis released a version of it on Sun Records in 1970.[46] Lewis started to play the song during his childhood upon request of his father, Elmo, and kept performing it as part of his frequent set numbers.[47] On his version, he replicated Rodgers' yodel.[48] It peaked at eleven in the Hot Country Singles chart in 1971.[49]
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