Digitalizzazione dei dibattiti parlamentari australiani, 1998 - Gruppo Componenti per lattine alimentari

Dati scientifici, volume 10, numero articolo: 567 (2023) Citare questo articolo

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La conoscenza pubblica di ciò che viene detto in parlamento è un principio della democrazia e una risorsa fondamentale per la ricerca in scienze politiche. In Australia, secondo la tradizione britannica, la registrazione scritta di ciò che viene detto in parlamento è conosciuta come Hansard. Sebbene l'Hansard australiano sia sempre stato disponibile al pubblico, è stato difficile da utilizzare per analisi di testo su larga scala a livello macro e micro perché era disponibile solo come PDF o XML. Seguendo l'esempio del progetto Linked Parliamentary Data che ha raggiunto questi risultati per il Canada, forniamo un nuovo database rettangolare, completo, di alta qualità che cattura gli atti dei dibattiti parlamentari australiani dal 1998 al 2022. Il database è disponibile al pubblico e può essere collegato ad altri set di dati come i risultati elettorali. La creazione e l'accessibilità di questo database consente l'esplorazione di nuove domande e costituisce una risorsa preziosa sia per i ricercatori che per i politici.

La documentazione scritta ufficiale dei dibattiti parlamentari, formalmente nota come Hansard1, svolge un ruolo fondamentale nel catturare la storia dei procedimenti politici e facilitare l'esplorazione di preziose questioni di ricerca. Originaria del parlamento britannico, la produzione dell'Hansard divenne tradizione in molti altri paesi del Commonwealth, come Canada e Australia2. Dato il contenuto e l’entità di questi documenti, essi hanno un significato, in particolare nel contesto della ricerca in scienze politiche. Nel caso del Canada, l’Hansard è stato digitalizzato dal 1901 al 20193. Avere una versione digitalizzata dell’Hansard consente ai ricercatori di condurre analisi del testo e modelli statistici. Seguendo l'esempio di quel progetto, in questo articolo presentiamo un database simile per l'Australia. Questo è composto da set di dati individuali per ogni giorno di seduta alla Camera dei Rappresentanti da marzo 1998 a settembre 2022, contenenti dettagli su tutto ciò che è stato detto in parlamento in una forma che può essere facilmente utilizzata dai ricercatori. Con lo sviluppo di strumenti per l’analisi di testi su larga scala, questo database fungerà da risorsa per comprendere il comportamento politico in Australia nel tempo.

Esiste un'ampia varietà di potenziali applicazioni di questo database. Ad esempio, in Australia esiste una notevole preoccupazione per il declino della “qualità” del dibattito sulle politiche pubbliche (in qualunque modo lo si possa definire). Il nostro set di dati potrebbe essere utilizzato per verificare se la situazione sta davvero peggiorando in particolari modi e, in caso affermativo, perché. Potremmo anche essere interessati a sapere se particolari sottopopolazioni sono adeguatamente rappresentate in ciò di cui si parla in parlamento. Ad esempio, si teme spesso che le aree regionali siano trascurate rispetto alle aree metropolitane. Ancora una volta, il nostro database potrebbe essere utilizzato per esaminare se ciò è cambiato nel tempo. Abbiamo sviluppato il nostro database in modo tale da poter essere collegato con database simili di altri paesi che consentirebbero un'analisi comparativa. Ad esempio, potremmo essere interessati a come cambia il focus politico di un parlamento alla luce di vari eventi globali come pandemie o guerre. Un collegamento internazionale fornisce un caso di confronto in cui le questioni interne sono diverse mentre quelle internazionali sono comuni. Come esempio di abilitazione di questo collegamento, abbiamo incluso gli ID PartyFacts (https://partyfacts.herokuapp.com) nel nostro database. Ciò dovrebbe consentire di collegare il nostro database con altri grandi progetti di raccolta di discorsi parlamentari, come ParlaMint4, ParlSpeech5, ParlEE6 e MAPLE7.

La Camera dei Rappresentanti australiana, spesso definita “la Camera”, svolge una serie di funzioni governative cruciali, come la creazione di nuove leggi e la supervisione della spesa pubblica8, cap. 1. I politici alla Camera sono indicati come Membri del Parlamento (MP). La Camera opera secondo una struttura camerale parallela, il che significa che ci sono due sedi di dibattito in cui si svolgono i procedimenti: la Camera e la Camera della Federazione. Le sedute della Camera seguono un ordine dei lavori predefinito, regolato da norme procedurali denominate ordini permanenti8, cap. 8. Una tipica giornata di seduta alla Camera prevede una serie di procedimenti programmati, tra cui dibattiti su affari governativi, dichiarazioni di 90 secondi membri e Tempo delle interrogazioni8, cap. 8. La Camera della Federazione è stata creata nel 1994 come sede di dibattito subordinata della Camera. Ciò consente una migliore gestione del tempo degli affari della Camera poiché i suoi lavori si svolgono contemporaneamente a quelli della Camera8, cap. 21. Le sedute della Camera della Federazione si differenziano da quelle della Camera per ordine dei lavori e ambito della discussione. Le questioni economiche discusse nella Camera della Federazione si limitano in gran parte alle fasi intermedie dello sviluppo delle leggi e agli affari dei deputati privati8, cap. 21. È la registrazione e la compilazione di questi atti su cui si basa Hansard, ed è essenzialmente, ma non del tutto, letterale.

/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p>/p> and serves as a container for the entire document. This parent node may have up to four child nodes, where the first child node contains details on the specific sitting day. Next, contains all proceedings of the Chamber, contains all proceedings of the Federation Chamber, and contains Question Time proceedings. The Federation Chamber does not meet on every sitting day, so this child element is not present in every XML file. The use of separate child nodes allows for the distinction of proceedings between the Chamber and Federation Chamber. The structure of the and nodes are generally the same, where the proceeding begins with which is followed by a series of debates. Debate nodes can contain a child node which has a child node nested within it. That said, sometimes is not nested within . Each of these three elements (i.e., , , and ) as well as their respective sub-elements contain important information on the topic of discussion, who is speaking, and what is being said. The node within each one contains the bulk of the text associated with that debate or sub-debate. A typical node begins with a sub-node, providing information on the MP whose turn it is to speak and the time of their first statement. Unsurprisingly, speeches rarely go uninterrupted in parliamentary debate settings — they are often composed of a series of interjections and continuations. These statements are categorized under different sub-nodes depending on their nature, such as or . The final key component of Hansard is Question Time, in which questions and answers are classified as unique elements. More detail on the purpose and processing of Question Time will follow./p> (highlighted in blue), followed by a child element (highlighted in yellow) with sub-child elements such as the date and parliament number, which are all highlighted in pink. Next, there is the child element containing everything that takes place in the Chamber, , which is also highlighted in yellow in Fig. 1. As previously mentioned, the first sub-node of is . The structure of this can be seen between the nodes highlighted in green in Fig. 1, where the content we parse from the business start is highlighted in orange./p> versus . The next key task stemmed from the fact that the raw text data were not separated by each statement when parsed. In other words, any interjections, comments made by the Speaker or Deputy Speaker and continuations within an individual speech were all parsed together as a single string. As such, the name, name ID, electorate and party details were only provided for the person whose turn it was to speak. There were many intricacies in the task of splitting these speeches in a way that would be generalizable across sitting days. Details on these are provided later./p> content, and some days did not have a Federation Chamber proceeding. To improve the generalizability of these scripts, if-else statements were embedded within the code wherever an error might arise due to a missing element. For example, the entire Federation Chamber block of code is wrapped in an if-else statement for each script, so that it only executes if what the code attempts to parse exists in the file./p> in all XML files prior to 14 August 2012. Having developed our first script based on Hansard from recent years, all XPath expressions for parsing Federation Chamber proceedings contain the specification. To avoid causing issues in our first script which successfully parses about 10 years of Hansard, we created a second script where we replaced all occurrences of with . After making this modification and accounting for other small changes such as timestamp formatting, this second script successfully parses all Hansard sitting days from 10 May 2011 to 28 June 2012 (inclusive)./p> are typically , and . The first child node contains data on the person whose turn it is to speak, and the second contains the entire contents of that speech –- including all interjections, comments, and continuations. After the element closes, there are typically a series of other child nodes which provide a skeleton structure for how the speech proceedings went in chronological order. For example, if the speech began, was interrupted by an MP, and then continued uninterrupted until the end, there would be one node and one node following the node. These would contain details on the MP who made each statement, such as their party and electorate./p> node. Rather than this single child node that contains all speech content, statements are categorized in individual child nodes. This means that unlike our code for parsing more current Hansards, we cannot specify a single XPath expression such as “chamber.xscript//debate//speech/talk.text” to extract all speeches, in their entirety, at once. This difference in nesting structure made many components of our second script unusable for processing transcripts preceding 10 May 2011, and required us to change our data processing approach considerably./p> node, we found that the most straightforward way to preserve the ordering of statements and to parse all speech contents at once was to parse from the element directly. The reason we did not use its child node is because every speech has a unique structure of node children, and this makes it difficult to write code for data cleaning which is generalizable across all speeches and sitting days. The challenge with parsing through the element is that every piece of data stored in that element is parsed as a single string, including all data, and all nested sub-debate data. For example, the data shown in Fig. 2 would be parsed as a single string preceding the speech content, like so:/p>

node, and used them to split statements wherever one of these patterns was found. After separating the statements, we were able to remove these patterns from the body of text. We also used this method of extracting and later removing unwanted patterns for other pieces of data which did not belong to the debate proceedings, such as sub-debate titles./p> child node, with sub-child nodes called and to differentiate the two. Questions in writing, however, are embedded in their own child node called at the end of the XML file./p> speeches used in all four scripts meant that all questions without notice content was already parsed in order. For the first two scripts, questions and answers were already separated onto their own rows. For the third and fourth scripts, just as we did with the rest of the speech content, we used those patterns of data preceding the text to separate questions and answers. Finally, since questions in writing exist in their own child node we were able to use the same parsing method for all scripts, which was to extract all question and answer elements from the child node./p> nodes to separate speeches. As evident in Fig. 3, nodes are nested within nodes, meaning that the patterns of data from interjection statements were separated out in the process. This meant that we did not need to create lists of names and titles for which to search in the text as we did before. However, we used the same list of general interjection statements on which to separate as was used in the first two scripts. We then did an additional check for statements that may have not been separated due to how they were embedded in the XML, and separated those out where needed. In particular, while most statements were categorized in their own child node and hence captured through pattern-based separation, some were not individually categorized, and had to be split manually in this step./p> nodes contain important data on the MP making each statement. As such, we could extract those data associated with each pattern by parsing one element inward, using the XPath expression “talk.start/talker”. We created a pattern lookup table with these data, and merged it with the main Hansard dataframe by the first pattern detected in each statement. Figure 6 provides an example of that lookup table. This approach enabled us to fill in missing data on each MP speaking using data extracted directly from the XML. Finally, we then used the AustralianPoliticians dataset to fill in other missing data, and flagged for interjections in the same manner as before./p> content in their own nodes that contain the voting data and division result. Since we focus primarily on the spoken Hansard content, our parsing scripts do not necessarily capture all divisions data from House proceedings. Our approach to parsing Hansard in the third and fourth scripts described in the Script Differences section naturally allowed for much of the divisions data to be added to our resulting files for 1998 to March 2011, however the parsing scripts used for May 2011 to September 2022 Hansard did not. To supplement our database and in an effort to fill this divisions data gap, we created an additional file containing all divisions data nested under the XPath “//chamber.xscript//division” from the Hansard files in our time frame. To produce this data file, for each Hansard XML we parsed the , , and child-nodes where they existed, extracted any timestamps where available, and did any additional data cleaning as necessary. We used a series of if-else statements in this script to account for variation in the structure of the node over time. Finally, we then added a date variable to distinguish between sitting days./p> element is the date. Every file passed this test, and we detected one discrepancy in an XML file from 03 June 2009, where its session header contained the wrong date. We validated that our file name and date was correct by checking the official PDF release from that sitting day./p>